#Embedded Systems Online Course

[questacademy]

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[zekatix]

Advanced Machine Learning Techniques for IoT Sensors

As we explore the realm of advanced machine learning techniques for IoT sensors, it’s clear that the integration of sophisticated algorithms can transform the way we analyze and interpret data. We’ve seen how deep learning and ensemble methods offer powerful tools for pattern recognition and anomaly detection in the massive datasets generated by these devices. But what implications do these advancements hold for real-time monitoring and predictive maintenance? Let’s consider the potential benefits and the challenges that lie ahead in harnessing these technologies effectively.

Overview of Machine Learning in IoT

In today’s interconnected world, machine learning plays a crucial role in optimizing the performance of IoT devices. It enhances our data processing capabilities, allowing us to analyze vast amounts of information in real time. By leveraging machine learning algorithms, we can make informed decisions quickly, which is essential for maintaining operational efficiency.

These techniques also facilitate predictive analytics, helping us anticipate issues before they arise. Moreover, machine learning automates routine tasks, significantly reducing the need for human intervention. This automation streamlines processes and minimizes errors.

As we implement these advanced techniques, we notice that they continuously learn from data patterns, enabling us to improve our systems over time. Resource optimization is another critical aspect. We find that model optimization enhances the performance of lightweight devices, making them more efficient.

Anomaly Detection Techniques

Although we’re witnessing an unprecedented rise in IoT deployments, the challenge of detecting anomalies in these vast networks remains critical. Anomaly detection serves as a crucial line of defense against various threats, such as brute force attacks, SQL injection, and DDoS attacks. By identifying deviations from expected system behavior, we can enhance the security and reliability of IoT environments.

To effectively implement anomaly detection, we utilize Intrusion Detection Systems (IDS) that can be signature-based, anomaly-based, or stateful protocol. These systems require significant amounts of IoT data to establish normal behavior profiles, which is where advanced machine learning techniques come into play.

Machine Learning (ML) and Deep Learning (DL) algorithms help us analyze complex data relationships and detect anomalies by distinguishing normal from abnormal behavior. Forming comprehensive datasets is essential for training these algorithms, as they must simulate real-world conditions.

Datasets like IoT-23, DS2OS, and Bot-IoT provide a foundation for developing effective detection systems. By leveraging these advanced techniques, we can significantly improve our ability to safeguard IoT networks against emerging threats and vulnerabilities.

Supervised vs. Unsupervised Learning

Detecting anomalies in IoT environments often leads us to consider the types of machine learning approaches available, particularly supervised and unsupervised learning.

Supervised learning relies on labeled datasets to train algorithms, allowing us to categorize data or predict numerical outcomes. This method is excellent for tasks like spam detection or credit card fraud identification, where outcomes are well-defined.

On the other hand, unsupervised learning analyzes unlabeled data to uncover hidden patterns, making it ideal for anomaly detection and customer segmentation. It autonomously identifies relationships in data without needing predefined outcomes, which can be especially useful in real-time monitoring of IoT sensors.

Both approaches have their advantages and disadvantages. While supervised learning offers high accuracy, it can be time-consuming and requires expertise to label data.

Unsupervised learning can handle vast amounts of data and discover unknown patterns but may yield less transparent results.

Ultimately, our choice between these methods depends on the nature of our data and the specific goals we aim to achieve. Understanding these distinctions helps us implement effective machine learning strategies tailored to our IoT security needs.

Ensemble Methods for IoT Security

Leveraging ensemble methods enhances our approach to IoT security by combining multiple machine learning algorithms to improve predictive performance. These techniques allow us to tackle the growing complexity of intrusion detection systems (IDS) in interconnected devices. By utilizing methods like voting and stacking, we merge various models to achieve better accuracy, precision, and recall compared to single learning algorithms.

Recent studies show that ensemble methods can reach up to 99% accuracy in anomaly detection, significantly addressing issues related to imbalanced data. Moreover, incorporating robust feature selection methods, such as chi-square analysis, helps enhance IDS performance by identifying relevant features that contribute to accurate predictions.

The TON-IoT dataset, which includes realistic attack scenarios and regular traffic, serves as a reliable benchmark for testing our models. With credible datasets, we can ensure that our machine learning approaches are effective in real-world applications.

As we continue to refine these ensemble techniques, we must focus on overcoming challenges like rapid system training and computational efficiency, ensuring our IDS remain effective against evolving cyber threats. By embracing these strategies, we can significantly bolster IoT security and protect our interconnected environments.

Deep Learning Applications in IoT

Building on the effectiveness of ensemble methods in enhancing IoT security, we find that deep learning applications offer even greater potential for analyzing complex sensor data.

By leveraging neural networks, we can extract intricate patterns and insights from vast amounts of data generated by IoT devices. This helps us not only in identifying anomalies but also in predicting potential failures before they occur.

Here are some key areas where deep learning excels in IoT:

Anomaly Detection: Recognizing unusual patterns that may indicate security breaches or operational issues.

Predictive Maintenance: Anticipating equipment failures to reduce downtime and maintenance costs.

Image and Video Analysis: Enabling real-time surveillance and monitoring through advanced visual recognition techniques.

Natural Language Processing: Enhancing user interaction with IoT systems through voice commands and chatbots.

Energy Management: Optimizing energy consumption in smart homes and industrial setups, thereby improving sustainability.

Frequently Asked Questions

What Machine Learning ML Techniques Are Used in Iot Security?

We’re using various machine learning techniques for IoT security, including supervised and unsupervised learning, anomaly detection, and ensemble methods. These approaches help us identify threats and enhance the overall safety of interconnected devices together.

What Are Advanced Machine Learning Techniques?

We’re exploring advanced machine learning techniques, which include algorithms that enhance data analysis, facilitate pattern recognition, and improve predictive accuracy. These methods help us make better decisions and optimize various applications across different industries.

How Machine Learning Techniques Will Be Helpful for Iot Based Applications in Detail?

We believe machine learning techniques can transform IoT applications by enhancing data processing, improving security, predicting failures, and optimizing maintenance. These advancements not only boost efficiency but also protect our interconnected environments from potential threats.

How Machine Learning Techniques Will Be Helpful for Iot Based Applications in Detail?

We see machine learning techniques enhancing IoT applications by enabling predictive analytics, improving decision-making, and ensuring robust security. They help us identify unusual patterns, streamline operations, and optimize resource management effectively across various sectors.

Conclusion

In conclusion, by harnessing advanced machine learning techniques, we’re transforming how IoT sensors process and analyze data. These methods not only enhance our ability to detect anomalies but also empower us to make informed decisions in real-time. As we continue to explore supervised and unsupervised learning, along with ensemble and deep learning approaches, we’re paving the way for more efficient and secure IoT systems. Let’s embrace these innovations to unlock the full potential of our connected devices.

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[neuailabs]

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[rahultandle]

https://www.cranesvarsity.com/courses/embedded-systems-course-online/

[hms-no-fun]

you were on cohost? i guess too late now, how was it for you?

cohost had its fair share of problems and i could often find the community there a bit too tumblr-core fingerwaggy if you know what i mean. but the site's dead now so it's kind of a moot point. what i find myself reflecting on most these days are the positives.

first, no numbers. i think their no numbers policy was probably a bit over-aggressive, but it quelled some of the rat race popularity contest aspect of social media that often makes it so tedious. i liked their tag tracking system, their robust content warning options, and the absence of infinite scroll. what i miss most about cohost is that their text editor supported CSS, which led to people programming elaborate text effects and puzzles and games in-site that harkened back to the days of flash animations. there was something in this combination of elements that drew out a rebellious creativity in users.

cohost came at a time when social media was across the board feeling terrible (and it's only gotten worse hahaha), particularly as someone who makes shit that relies on you clicking links that take you away from the website or app. algorithms hate this and punish it. users also just seem kind of lazy and disinterested in using the internet so much as letting the internet happen to them passively. but when a post of mine went viral on cohost, people engaged with it. it wasn't just likes and shares, it was comments and additions. it felt like a place that (at its best) encouraged actual conversation and the development of new ideas among like-minded peers. when my posts did well and i included a donation link, people gave me money. it felt genuinely like a website that COULD support professional blog work in a way that was more customizable even than substack yet still RSS friendly, and the Following tab which let you easily see posts of specific users was a REVELATION, like a mini RSS reader within the website itself.

but the enterprise was unsustainable for various reasons (not all of them outside the dev crew's control) and the haters got what they wanted. now our big social media alternative is bluesky, a website that dares to ask the question "what if there was another twitter?" the answer is that it fucking sucks. i hate microblogs so much dude, why on EARTH are we still acting like these disambiguited 300-character-limit posts are the most preferable means of social communication online??? why would you set out to make a better twitter and then deliberately choose to replicate literally every aspect of the user experience that encouraged low-information high-drama conflict fabrication? WHY WOULD YOU MAKE A VERSION OF TWITTER WHERE YOU CAN EASILY LOOK UP THE ACCOUNT OF EVERYONE WHO HAS YOU BLOCKED AND IT'S SUPPOSED TO BE A FEATURE NOT A BUG???????? i just don't get it. i don't even get the optimism of the early adopters. i've seen people decry the post-election decay of the platform like "of course the cishets come in to ruin a community that was defined by trans & queer people" i'm sorry HELLO???????? from literally day zero bluesky was aiming to be a hands-off centrist IPO-friendly tech startup, there was never anything structurally embedded within the platform itself to keep this kind of decay from happening, you just happened to be on there when there were dramatically fewer users most of whom were curious tech enthusiasts. seriously, how have we not learned this lesson yet? you can't define a digital culture by the vibes of random user behavior! unless you have LAWS and GUIDELINES whereby you fucking BAN people for being shitheads, unless you enforce an actual code of conduct and punish bigoted speech and design a system that encourages constructive conversation, you are always always ALWAYS going to wind up at unhinged facebook boomer slop!

the death of cohost and the utterly predictable decay of bluesky are a big part of the reason why i've been posting so much more on tumblr. this is like the last bastion of anything even remotely resembling the old web, with its support of longposts and tagging and how easy it is to find random hobbyists doing cool shit you never knew existed before. like, yeah, you have to search that shit out and tailor your feed to not drive you crazy, but that's what i like about it!!! i am an adult with agency who understands that life is complicated and as such i expect to have to put some work into making my experience with a website positive! but in the hellworld of the iphone everything is walled garden apps for aggregating content where the content and its creators are structurally established as infinitely replaceable and uniquely worthless punching bags to be used and cast aside. everyone's given up on moderation and real jobs don't exist anymore especially if you happen to work in the "creative economy" IE are a writer or critic or artist or hobbyist of literally any kind. we've given up on expecting anything from the rich moneyboys who own and profit immensely off of the platforms whose value we literally create!!! especially now with the rise of "AI" grifters, whose work has ratcheted good old fashioned casual sexism and racism and homophobia up to levels not seen in such mainstream spaces since the early 2000s.

i like tumblr because i don't have to use a third party app to get & answer asks at length, and because it is a visual artist friendly platform where i won't be looked at funny for reblogging furry postmodernism or transgender homestuck OCs. it is a site that utterly lacks respectability and that's what makes it even remotely usuable. unfortunately it also sucks! partly it sucks because this place was ground zero for the rise of puritanical feminist-passing conservatism in leftist spaces, so it's like a hyperbolic time chamber for brain-melting life or death discourse about the most inconsequential bullshit you could ever imagine. but it also sucks because it's owned by a profit-motivated moneyboy who has consistently encouraged a culture of virulent transphobia and frequently bans trans women who call this out. so like, yeah, this place is cool compared to everywhere else, but it is exactly like everywhere else in that is also on a ticking clock to its own inevitable demise. the owners of this website will destroy everything that makes it interesting and will EAGERLY delete the nearly twenty years (!!!!!!) of posts it's accumulated the instant it will profit them to do so. this will be immensely unpopular and everyone will agree it's a tragedy and it won't matter. the culture and content of a social media platform is epiphenomenal to its rote economic valuation. i mean, obviously it isn't, zero of these massive tech companies would be what they are if so many people weren't so eager to give their time and labor away for free (and yes, writing a dumb dick joke on tumblr IS a form of labor in the same way that doing a captcha is labor, just because it's a miniscule contribution in an economy of scale doesn't mean you didn't contribute!), but once a tech company reaches a certain threshold its valuation ceases to be tethered to anything that actually exists in reality.

all of which is why i remember cohost with a heavy heart. yeah, it was imperfect. it was also independently owned, made with the explicit goal of creating a form of social media that actually tries not to give you a lifelong anxiety disorder so it can sell you homeopathic anti-anxiety sawdust suppositories. for the brief window of time when it was extant, i was genuinely hopeful for the future of being a creative on the internet. part of why i spend so much time on godfeels, a fucking homestuck fanfiction with no hope of turning a profit or establishing mainstream legitimacy, is that my readers actually ENGAGE with the material. what brought me back to using this website consistently was precisely the glut of godfeels-related questions i got, and the exciting conversations that resulted from my answers. meanwhile i put so many hours into my videos and even when they do well numerically, i barely see any actual engagement with the material. and that is a deliberate design choice on the part of youtube! that is the platform functioning as intended!! it sucks!!!

what the memory of cohost has instilled in me is a neverending distaste for the lazy unambitious also-rans that define the modern internet. i remember the possibility space of the early web and long for the expressiveness that even the most minor of utilities offered. we sacrificed that freedom for a convenience which was always the pretense for eventually charging us rent. i am thinking a lot these days about what a publicly funded government administrated social media utility would look like. what federal open source standards could look in an environment where the kinds of activities a digital ecosystem can encourage are strictly regulated against exploitation, bigotry, scams, and literal gambling. what if there was a unionized federal workforce devoted to the administration of internet moderation, which every website above a certain user threshold must legally take advantage of? i like to imagine a world where youtube isn't just nationalized but balkanized, where you have nested networks of youtubes administrated for different purposes by different agencies and organizations that operate on different paradigms of privacy and algorithmic interaction. imagine that your state, county, and/or city has its own branch of youtube meant to specifically highlight local work, while also remaining connected to a broader national network (oops i just reinvented federation lmao). imagine a world where server capacity is a publicly owned utility apportioned according to need and developed in collaboration with the communities of their construction rather than as a deliberate exploitation of them. our horizons for these kinds of things are just so, so small, our ability to imagine completely captured by capitalist realism, our willingness to demand services from our government simply obliterated by decades of cynical pro-austerity propaganda. i imagine proposing some of this stuff and people reacting like "well that's unrealistic" "that'll never happen" "they'd just use it for evil" and i am just SO! FUCKING! TIRED!!!!

like wow you're soooooo cool for being effectively two steps left of reagan, i bet you think prison abolition and free public housing are an impossible pipedream too huh? and exactly what has that attitude gotten you? what've you gained by being such a down to earth realist whose demands are limited by the scope of what seems immediately possible? has anything gotten better? have any of the things you thought were good stayed good? is your career more stable, your political position more safe, your desire to live and thrive greatly expanded? or do you spend every day in a cascading panopticon of stress and collapse, overwhelmed to the point of paralysis by the sheer magnitude of what it's cost us to abandon the future? you HAVE to dream. you HAVE to make unrealistic demands. the fucking conservatives have been making unrealistic demands forever and look, they're getting everything they want even though EVERYONE hates them for it! please i'm begging you to see and understand that what's feasible, what's reasonable, what's realistic, are literally irrelevant. these things only feel impossible because we choose to believe The Adults (and if you're younger than like 45, trust me, to the ruling class you are a child) whose bank accounts reflect just how profitable it is to convince us that they're impossible. all those billions of dollars these fuckers have didn't come from nowhere, it was stolen from all of us. there is no reason that money can't and shouldn't be seized and recirculated back into the economy, no reason it can't be used to fund a society that is actually social, where technological development is driven not by what's most likely to drive up profits next quarter but by what people need from technology in their daily lives.

uh so yeah basically that's my opinion of cohost lmao

[unregisteredskybox]

[@ysines becuz u asked :D] im gonna preface this rant by saying i think side order was GREAT!!!! i love roguelikes i love splatoon this was a dlc MADE for me,

that being said! the lore was obviously, unfortunately, not the focal point of the dlc, especially the final boss being [spoilers!] another sentient ai. i love the little guy, but tartar [my wife] did it better. so UNDER THE CUT will be a long rant as to what i would make for the final boss of the DLC, along with some art I made for it!!! Oh, and that final boss?

Order, a sentient collection of Eight's memories that deems ITSELF to be the real copy

alright, now that i have your attention, let me go into depth as to how this all began, side order spoilers obviously:

Marina created the Memverse to help all the octolings from the metro of course, but more specifically, her friend Eight. The entire memverse was based on their memories, using them as the "blueprint" for all memcake related technology, since theirs were fully intact. Not only that, but since Eight was not only unsanitized, in a right state of mind, and an incredibly capable fighter, they were the perfect basis for those CLIMBING the tower. if the memverse is brain surgery, than Eight's brain was the example used. makes sense? This is where thing's get weird, however. Eight's memories are embeded within the memverse itself, interconnected with all aspects of it. Functionally speaking, a part of their SOUL was in the memverse, a soul with lots of desires, dreams, and determination. They fought through kamabo co. after all, their soul wouldn't be so easily tamed. Marina allotted too much control over to Eight's memories, so as soon as the memverse was online, they were alive. Alive...

And alone.

The memverse was just booting up, and considering how big it was, it would likely take hours, maybe even days. Days that Not-Eight would have to spend wandering an unfished world alone, devoid of any meaningful colour. It was designed to be monochrome as it was easier to retain memories when climbing the spire, without significant colour to distract the climber. Worst part was, this individual was eight's memories BEFORE octo expansion, so the last thing they remember is falling after fighting agent 3, waking up here. Through time, other memories would spark creation within the world, from the sanitized octolings who helped on the project, but it was still a long and lonely time for Not-Eight. However, as I said, they're the blueprint for this world, and was interconnected with it, so they had a form of control. It wasn't a conscious decision, but rather, the unbearable feeling of loneliness caused the simulation to pull people IN, hoping to satiate the desire for connection the god of this world demanded. And, with our Eight also being integral to the memverse, the system decided the perfect fit would be to bring in their best bud Agent 4! ...Who Not-Eight didn't know because they've never met.

But, after a quick explanation, Four, smart as they are, picks up on the situation: something went wrong in the Memverse, and Eight only remembers her previous memories, and not her current ones. Alright, they've got it completely wrong, but it's the logical conclusion. The two do find solace in each other, however, as they wander the Memverse searching for...anything really. As this happens though, something starts to happen to Not-Eight. This entire time, they've felt like something was missing. Like when you wake up from a dream, and feel like you can remember it exactly, yet it immediately fades away. That, but constantly. They assume Four's story is correct, since it would explain the feeling, but it doesn't offer them any comfort. There's also Not-Eight's emotional state, since they've been wandering the memverse for days now, and Four's only done it for maybe a few hours. It's taken a toll on their mind, and by proxy, the Memverse itself. Remember, it's connected to them, their loneliness was why Four was here in the first place. As such, with their desire to be fulfilled, to remember something, the Memverse starts to overwork itself; it brings the spire into existence, the Jelletons, all of the challenges, much faster than it should, all for its God that doesn't even know it's a god in the first place. With this speed comes mistakes, or in computer terms, glitches. Just as Not-Eight's mental state effects the memverse, the memverse's stability effects Not-Eight. They start to, if only gradually, undergo a process known as Bleaching; when a Soul and Body are separated into two individual beings, the soul in the memverse, and the body outside of it. [This replaces greyscaling.] But, Not-Eight doesn't have a body, just a simulated one to house their soul. That means, while attempting to climb the spire with four, they start to deteriorate. Pieces of them glitch away, corals grow and cover their face, and features just disappear. It's an incredibly painful process, one that Four doesn't really understand, so they try to solve it in the only way they know how: getting to the top. It's hard, especially considering they have to carry Not-Eight up there, and have no colour chips [Only weapons they summoned the same way Pearl did], but they make it to the control room. Pulling up a monitor, they scroll to a section covering the Admins of the spire. Marina, Pearl, Four themselves, and...two instances of Eight. One of them is glitching out, so that's the one Four goes for, not bothering to question why there were two. They click the button to reset the palette, but...that was probably the worst thing they could've done. In an instant, Not-Eight's mind was flooded with the code of the entire memverse, it's innerworkings, what it was currently processing, and their identity. They knew within an instant that they were just MEMORIES, a shadow of another person. Yet, they also knew how much power they had over the world. Without another word, they immediately Bleached Four, creating the Parallel Canon boss and Order Defense Force. They knew that the "real" Eight would come for them, to subsume them, to replace them, so they would need defenses. Though they acted like a tough general on the outside, in reality, Order was horrified. They were, mentally, a fourteen-year old child who failed to escape to the surface and instead fell into what was practically Hell. A cold, barren landscape with no colour or emotions, a place where they would die by being assimilated into another person. The mask placed on the Parallel Canon boss wasn't something to control them, as they already had that power. Rather, it was to make other beings look more like themselves after they began to decompose. This, is Order, the commander of the spire:

The red bits on their body are pieces they can no longer use due to the Bleaching, which is basically trying to separate their soul in two, considering they don't have a body. All facial recognition they once had has been wiped clean, and they're more coral than octoling at this point. Now is when Eight and the rest of the gang enter the memverse, but how Order presents themself is different. They're still a dignified smoke cloud, as they were after Marina, but they harbor an irrational sense of hatred towards Eight, one that isn't cold or orderly. Boss fights are now, as many people have suggested, Eight fighting the person the palette belongs to. Inky clones of Marie or Big man, who dissipate into a cloud of smoke once you defeat them, with Order taunting/insulting Eight after the fact. However, palette orders are slightly changed, as the last one you get before Eights is Four's. Now, the Parallel Canon boss up to this point would've been the hairless clones specifically, because Order is saving Four for last. Once Eight reaches the top, Order does another monologue, and brings out Four in hopes that Eight's emotional attachment to them would make them give up. [It does not, as Eight is INCREDIBLY used to fighting their brainwashed friends.] Once Four is defeated, they're freed from the Bleaching/mind control, and exposes Order's identity in their fit of rage. Now, Order did genuinely like Four, so seeing them express such hatred for them puts them in a really terrible mood, especially considering Eight is one step closer to replacing them.

at this point, Order freaks out, and Eight probably would as well, considering that they look exactly like each other [Though Order's freakout is more anger and Eight's is more confusion.] Order's one goal now is to kill Eight and replace them before they can do the same. It probably has some sort of AM I Have No Mouth and I Must Scream esque monologue [can you see the inspiration? i love it so much] and deems itself to be the one true "eight." After escaping the tower, with a bit of exposition from both Four and Marina, the entire group basically figures out what's going on. Their respective reactions, however, are a little different, mainly between Eight and everyone else. Most of the group feels sympathetic for Order, as they're a 14 year old who's only known loneliness, the fake sunlight, and is currently at risk of being replaced as a person. Eight, however, has NO sympathy for Order whatsoever, an opinion they would definitely voice. They toiled and troubled through Kamabo Co and the spire just to get their memories back, but now their friends are arguing that they shouldn't? That they should remain without memories just to keep a fake person alive? I've been writing this with more of a story perspective than a gameplay one, so this would probably cause some divide in the group. How the Memverse works to me is after freeing Marina, all of them could come and go from the simulation as they please, like a normal VR. And, because I loooove angst, I could see Eight sneaking into the simulation when everyone else is gone and fighting Order themselves, since no one agrees with them.

Here's where I split the timeline a little, because honestly? I don't know how this should end! I could see two options, option 1. With plenty of time and convincing, they learn to coexist, Order eventually becoming like a little sister to Eight and the two of them living in harmony, completing each other. Option 2? One of them kills the other, permanently, and basically absorbs their mind, memories and bodies, just fitting with the personality of whoever won. IDK!!! I could draw smth for both maybe? Or if you, the lovely reader have any ideas???

And if you have any questions about this (or the aforementioned ideas) don't be afraid to drop an ask!!!!!!!! ooough that was long. thanks for reading : D

[mariacallous]

Britain is burning. The recent weeks of far-right riots have seen mobs assembling outside mosques and hotels housing asylum-seekers; the burning of public libraries; and an uptick in targeted racist violence and vandalism. Sparked by the tragic deadly stabbings of three young girls in the town of Southport, the incident has been sickeningly exploited by anti-immigrant and anti-Muslim groups, which have spread disinformation online and garnered support from prominent far-right figures.

Less than two months after a new Labour government took office, the issue of immigration has already taken center stage. Prime Minister Keir Starmer now faces the steep challenge of tackling the root causes of Britain’s toxic relationship with immigration.

For years now, the issue of immigration has been at the heart of the British predicament, and in the wake of Brexit, the normalization of far-right rhetoric has increasingly embedded itself in Britain’s media and political landscape.

The Labour Party must not be blown off course by the recent riots. It should instead capitalize on this moment—using it to carve out a new, humane immigration policy.

Even though Starmer’s government has pledged to increase the number of deportations of those who do not have the right to stay in the country, there have been some important changes to Britain’s immigration policies since Labour came into power.

Most prominently, on the first day of his premiership, Starmer scrapped the controversial Rwanda bill that entailed sending asylum-seekers from the United Kingdom to the East African nation. Introduced by former Prime Minister Boris Johnson in 2022, many considered the policy to be a cynical maneuver rather than a serious solution to address the country’s broken immigration system. New Home Secretary Yvette Cooper called it “a complete con,” which she told Parliament had cost the British taxpayers 700 million pounds (about $918.4 million)—a considerable sum of money given that no asylum-seeker ever set foot in Rwanda.

Perhaps the only enduring image of this failed Rwanda policy was a photo of the Conservative Party’s former Home Secretary Suella Braverman joyfully laughing in a center in Rwanda meant to house asylum-seekers. The daughter of immigrant parents who migrated to Britain from East Africa celebrating her “dream” of sending vulnerable asylum-seekers to one of the most repressive African countries was a stark symbol of the cruel and ineffective anti-migrant policies of the recent Tory era.

Last month, after Starmer spoke about “resetting” Britain’s approach to immigration in a way that respects international human rights standards, Labour also announced plans to permanently shut down the controversial Bibby Stockholm, a barge moored off the coast of Dorset that is used to hold asylum-seekers. In a surprise appointment, Starmer then chose Richard Hermer, a distinguished human rights lawyer who began his career at famed human rights firm Doughty Street Chambers, as his attorney general.

Another sign of change at the Home Office is that it now refers to migrants as “irregular” rather than “illegal,” a term routinely used under Tory governments that implied criminality and reinforced harmful stereotypes.

This is the sort of humane approach that Britain needs—only a much larger scale. Though these small changes were announced before the recent riots began, the question remains whether the Labour Party—even with its dark past—has the courage to transform Britain’s troubled relationship with immigration going forward. A lasting solution would address the spread of deceptive disinformation aimed at sowing hatred while also advocating for a truly compassionate and ethical immigration system.

For instance, Starmer could officially repeal the Illegal Migration Act, which was passed in July last year by the Tory-led government. The law allowed the government to deny the right of asylum to migrants who had arrived in the U.K. irregularly. It stated that the government could instead detain and deport refugees to their home countries or “safe” third countries (such as Rwanda). The controversial law was criticized by several human rights groups as well as the United Nations, which described it as an “asylum ban” that penalized vulnerable refugees by effectively closing off safe and legal pathways for those escaping persecution, violence, or conflict. Although the International Rescue Committee reports that the Labour Party has “effectively ended” enforcement of the law, it remains on the books.

In addition to scrapping the Tory-era act, the Labour government should also look to tackle the backlog of asylum cases. According to the latest Home Office data, there are more than 118,000 people waiting for an initial decision on their asylum applications. To truly bring down these figures, Starmer will need to do a lot more to reform a broken system that leaves thousands of vulnerable people trapped in destitution.

His government can seek real improvements in the asylum process by expanding safe routes, ensuring fair hearings, and demonstrating compassion and humanity. To focus on longer-term solutions, Starmer should prioritize Britain’s efforts to address the root causes of the global conflicts that drive many people to make perilous journeys in the first place.

Beyond repairing the asylum system, the Labour government could also uphold the rights of Britons of migrant background by revoking the Nationality and Borders Act that was passed in 2022, which creates a two-tiered system of citizenship, making naturalized British citizens—such as myself—second-class citizens.

The act grants the state the power to strip Britons of citizenship without giving them notice. This extreme measure makes Britain an outlier among liberal democracies—and unfairly targets its own citizens, especially British Muslims, even if their families have been in the country for generations.

Citizenship-stripping powers are not new in the United Kingdom, having been weaponized by both Labour and Tory administrations post-9/11. In the past two decades, hundreds of Britons have been stripped of their citizenships.

As the historian Hannah Arendt famously said, “citizenship is the right to have rights,” and the British state has weaponized citizenship in the name of security. Starmer has a rare opportunity to fix this.

Finally, Labour’s immigration policies ought to focus on the most vulnerable and impacted group: unaccompanied children. A recent data investigation conducted by Lost in Europe, a cross-border journalism collective, found that across 13 European countries, including Germany and Italy, more than 50,000 unaccompanied child migrants went missing between 2021 and 2023.

Though the British Home Office is yet to release specific numbers regarding the United Kingdom (despite a pending Freedom of Information Act request), we know that unaccompanied minors migrating to Britain remain at increased risk of gang recruitment, workplace exploitation, and modern slavery.

Another report conducted by a group of nongovernmental organizations earlier this year showed that hundreds of child refugees who had experienced abuse and violence were often placed in adult prisons after the Home Office wrongly assessed their ages. To make matters worse, British tabloids often disregard or question the ages of migrant children—making a mockery of the country’s laws intended to safeguard the identities of minors, especially those in search of safety.

These depictions of migrants in Britain have dangerous consequences, and they often act as a precursor to discrimination and violence. Britain has been here before.

More than 24 years after the infamous Oldham riots of 2001, which saw a brief period of racial rioting in a town near Manchester that spurred on the country’s far right, Britain has yet to learn from its mistakes.

The easy talk of race and civil war—most recently invoked by Elon Musk—plays into standard far-right tropes about the country, but the reality is that Britain has absorbed migrants much more effectively than many of its European neighbors, and its capital is largely a tolerant and multiethnic place. This is a story that is rarely told by irresponsible media figures and politicians who have whipped up far-right extremists for far too long.

As a member of Parliament, Starmer represents the Holborn and St Pancras seat, one of the most diverse areas in inner-city London. My family arrived in this constituency as refugees from Somalia almost 30 years ago. I grew up on a council estate in Camden next to pretty, tree-lined Edwardian terraced houses worth millions. It was a place of poverty and friendship—a place where Irish, Bangladeshi, Kosovar, and Somali kids mixed together, speaking multicultural London English, listening to garage music, playing soccer, and drinking in local pubs.

There were tensions when I was growing up—for example, in Somers Town, where I went to school in the mid-1990s. The fascist, far-right British National Party (BNP) tried to capitalize on the tragic killing of Richard Everitt, a white boy, in 1994 by a group of Bangladeshi boys. At one point, a far-right mob firebombed halal butchers on a street lined with Asian shops. But the incident had no real long-term impact, and the community moved on.

While these recent riots may hark back to those days, unlike the BNP of the 1990s, these disparate far-right groups have far more power today. They are bolstered by social media algorithms and support from online extremists, established media, and some of the billionaires who operate those very platforms. They systematically spread their hate.

It is these forces that seek to warp and destabilize British culture rather that the tiny minority of asylum-seekers and larger group of regular migrants who seek to make their lives in Britain. Labour must not fall into their trap and let British democracy be undermined.

[shalu620]

Why Python Will Thrive: Future Trends and Applications

Python has already made a significant impact in the tech world, and its trajectory for the future is even more promising. From its simplicity and versatility to its widespread use in cutting-edge technologies, Python is expected to continue thriving in the coming years. Considering the kind support of Python Course in Chennai Whatever your level of experience or reason for switching from another programming language, learning Python gets much more fun.

Let's explore why Python will remain at the forefront of software development and what trends and applications will contribute to its ongoing dominance.

1. Artificial Intelligence and Machine Learning

Python is already the go-to language for AI and machine learning, and its role in these fields is set to expand further. With powerful libraries such as TensorFlow, PyTorch, and Scikit-learn, Python simplifies the development of machine learning models and artificial intelligence applications. As more industries integrate AI for automation, personalization, and predictive analytics, Python will remain a core language for developing intelligent systems.

2. Data Science and Big Data

Data science is one of the most significant areas where Python has excelled. Libraries like Pandas, NumPy, and Matplotlib make data manipulation and visualization simple and efficient. As companies and organizations continue to generate and analyze vast amounts of data, Python’s ability to process, clean, and visualize big data will only become more critical. Additionally, Python’s compatibility with big data platforms like Hadoop and Apache Spark ensures that it will remain a major player in data-driven decision-making.

3. Web Development

Python’s role in web development is growing thanks to frameworks like Django and Flask, which provide robust, scalable, and secure solutions for building web applications. With the increasing demand for interactive websites and APIs, Python is well-positioned to continue serving as a top language for backend development. Its integration with cloud computing platforms will also fuel its growth in building modern web applications that scale efficiently.

4. Automation and Scripting

Automation is another area where Python excels. Developers use Python to automate tasks ranging from system administration to testing and deployment. With the rise of DevOps practices and the growing demand for workflow automation, Python’s role in streamlining repetitive processes will continue to grow. Businesses across industries will rely on Python to boost productivity, reduce errors, and optimize performance. With the aid of Best Online Training & Placement Programs, which offer comprehensive training and job placement support to anyone looking to develop their talents, it’s easier to learn this tool and advance your career.

5. Cybersecurity and Ethical Hacking

With cyber threats becoming increasingly sophisticated, cybersecurity is a critical concern for businesses worldwide. Python is widely used for penetration testing, vulnerability scanning, and threat detection due to its simplicity and effectiveness. Libraries like Scapy and PyCrypto make Python an excellent choice for ethical hacking and security professionals. As the need for robust cybersecurity measures increases, Python’s role in safeguarding digital assets will continue to thrive.

6. Internet of Things (IoT)

Python’s compatibility with microcontrollers and embedded systems makes it a strong contender in the growing field of IoT. Frameworks like MicroPython and CircuitPython enable developers to build IoT applications efficiently, whether for home automation, smart cities, or industrial systems. As the number of connected devices continues to rise, Python will remain a dominant language for creating scalable and reliable IoT solutions.

7. Cloud Computing and Serverless Architectures

The rise of cloud computing and serverless architectures has created new opportunities for Python. Cloud platforms like AWS, Google Cloud, and Microsoft Azure all support Python, allowing developers to build scalable and cost-efficient applications. With its flexibility and integration capabilities, Python is perfectly suited for developing cloud-based applications, serverless functions, and microservices.

8. Gaming and Virtual Reality

Python has long been used in game development, with libraries such as Pygame offering simple tools to create 2D games. However, as gaming and virtual reality (VR) technologies evolve, Python’s role in developing immersive experiences will grow. The language’s ease of use and integration with game engines will make it a popular choice for building gaming platforms, VR applications, and simulations.

9. Expanding Job Market

As Python’s applications continue to grow, so does the demand for Python developers. From startups to tech giants like Google, Facebook, and Amazon, companies across industries are seeking professionals who are proficient in Python. The increasing adoption of Python in various fields, including data science, AI, cybersecurity, and cloud computing, ensures a thriving job market for Python developers in the future.

10. Constant Evolution and Community Support

Python’s open-source nature means that it’s constantly evolving with new libraries, frameworks, and features. Its vibrant community of developers contributes to its growth and ensures that Python stays relevant to emerging trends and technologies. Whether it’s a new tool for AI or a breakthrough in web development, Python’s community is always working to improve the language and make it more efficient for developers.

Conclusion

Python’s future is bright, with its presence continuing to grow in AI, data science, automation, web development, and beyond. As industries become increasingly data-driven, automated, and connected, Python’s simplicity, versatility, and strong community support make it an ideal choice for developers. Whether you are a beginner looking to start your coding journey or a seasoned professional exploring new career opportunities, learning Python offers long-term benefits in a rapidly evolving tech landscape.

[sindhu14]

What is Python, How to Learn Python?

What is Python?

Python is a high-level, interpreted programming language known for its simplicity and readability. It is widely used in various fields like: ✅ Web Development (Django, Flask) ✅ Data Science & Machine Learning (Pandas, NumPy, TensorFlow) ✅ Automation & Scripting (Web scraping, File automation) ✅ Game Development (Pygame) ✅ Cybersecurity & Ethical Hacking ✅ Embedded Systems & IoT (MicroPython)

Python is beginner-friendly because of its easy-to-read syntax, large community, and vast library support.

How Long Does It Take to Learn Python?

The time required to learn Python depends on your goals and background. Here’s a general breakdown:

1. Basics of Python (1-2 months)

If you spend 1-2 hours daily, you can master:

Variables, Data Types, Operators

Loops & Conditionals

Functions & Modules

Lists, Tuples, Dictionaries

File Handling

Basic Object-Oriented Programming (OOP)

2. Intermediate Level (2-4 months)

Once comfortable with basics, focus on:

Advanced OOP concepts

Exception Handling

Working with APIs & Web Scraping

Database handling (SQL, SQLite)

Python Libraries (Requests, Pandas, NumPy)

Small real-world projects

3. Advanced Python & Specialization (6+ months)

If you want to go pro, specialize in:

Data Science & Machine Learning (Matplotlib, Scikit-Learn, TensorFlow)

Web Development (Django, Flask)

Automation & Scripting

Cybersecurity & Ethical Hacking

Learning Plan Based on Your Goal

📌 Casual Learning – 3-6 months (for automation, scripting, or general knowledge) 📌 Professional Development – 6-12 months (for jobs in software, data science, etc.) 📌 Deep Mastery – 1-2 years (for AI, ML, complex projects, research)

Scope @ NareshIT:

At NareshIT’s Python application Development program you will be able to get the extensive hands-on training in front-end, middleware, and back-end technology.

It skilled you along with phase-end and capstone projects based on real business scenarios.

Here you learn the concepts from leading industry experts with content structured to ensure industrial relevance.

An end-to-end application with exciting features

Earn an industry-recognized course completion certificate.

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[questacademy]

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[zekatix]

Top 10 Tips for IoT and AI Learning

As we navigate the evolving landscapes of IoT and AI, it’s crucial we establish a solid foundation to enhance our learning journey. By focusing on essential programming skills, engaging in practical projects, and tapping into online resources, we can cultivate a comprehensive understanding of these technologies. Additionally, connecting with like-minded individuals in vibrant communities can significantly enrich our experience. But that’s just the beginning; there are more strategies we can adopt to truly excel. What are some specific tips that can elevate our efforts even further?

Build Programming Foundations

Building strong programming foundations is essential for anyone looking to excel in IoT and AI. We should start by mastering programming languages commonly used in these fields, such as Python and JavaScript. These languages not only help us understand the underlying concepts but also allow us to build innovative applications.

Next, we need to grasp the basics of data analysis, as it’s crucial for making sense of the vast amounts of data that IoT devices generate. Engaging with hands-on projects can help bridge the gap between theory and practical application, so let’s actively seek out opportunities to work on real-world problems.

Additionally, joining forums and communities can enhance our learning experience. By sharing insights and solutions with others, we deepen our understanding and stay motivated.

Staying updated with industry trends is just as important; subscribing to relevant publications and attending webinars keeps us informed about the latest advancements.

Explore Online Courses

Exploring online courses is a fantastic way for us to deepen our understanding of IoT and AI. These courses often provide a solid foundation in fundamental concepts, applications, and implications of IoT technology.

We can expect to learn about the interconnected network of devices and sensors, gaining insights into real-world applications that impact various sectors.

Most importantly, structured curricula designed by experts ensure we’re learning effectively. Live sessions with top educators allow us to engage actively, while interactive chats foster discussions with both instructors and peers.

Quizzes and practice tests help us track our progress and solidify our knowledge.

Moreover, joining these courses gives us exclusive access to a supportive community. We can network with like-minded individuals, collaborate on problem-solving, and share ideas in dedicated chat groups.

Once we complete a course, we receive a certificate that showcases our skills on platforms like LinkedIn, enhancing our professional profiles and job prospects.

Engage in Hands-On Projects

After gaining theoretical knowledge through online courses, engaging in hands-on projects allows us to put that learning into action.

By working on practical projects, we can deepen our understanding of IoT and AI while also honing our programming and data analysis skills. These projects help bridge the gap between theory and practice, enabling us to see the real-world applications of what we’ve learned.

Here are four engaging project ideas to consider:

Smart Parking System: Create a system that analyzes traffic volume and directs drivers to available spots using IoT sensors.

Healthy Diet Monitoring: Develop an application that tracks food purchases and suggests healthier options based on student data.

Attendance Monitoring: Implement IoT devices to automate student attendance tracking for greater efficiency.

Interactive Learning Tools: Build tools that employ IoT devices to enhance hands-on learning experiences in classrooms.

Join IoT and AI Communities

Joining IoT and AI communities can significantly enhance our learning journey by connecting us with like-minded individuals who share our interests.

These communities offer us exclusive access to structured courses, networking opportunities, and a continuous learning environment. By engaging in live learning sessions with top educators, we can deepen our understanding through interactive chats and expert-designed curricula.

Participating in community discussions and events allows us to collaborate and support one another. We can exchange ideas, troubleshoot problems, and gain insights from diverse backgrounds.

This rich interaction not only broadens our knowledge but also strengthens our professional networks. Plus, we’ll find exclusive chat groups that facilitate ongoing conversations with peers and instructors.

As we complete courses, we’ll receive certificates that can be showcased on LinkedIn, enhancing our professional credibility and career advancement opportunities.

The availability of academic resources like practice tests and support materials ensures we’re always prepared for the next challenge.

Stay Updated With Trends

Staying updated with trends in IoT and AI is essential for anyone looking to thrive in these rapidly evolving fields. By keeping our knowledge current, we can make informed decisions and seize opportunities as they arise.

Here are four key actions we can take to stay ahead:

Follow Industry News: Subscribe to relevant publications, blogs, and newsletters that cover the latest advancements in IoT and AI. Engaging with this content can provide valuable insights.

Attend Webinars and Conferences: Participating in online and in-person events helps us learn from industry leaders and network with like-minded individuals, enhancing our understanding of current trends.

Engage in Online Communities: Join forums and social media groups focused on IoT and AI discussions. Sharing experiences and learning from others can deepen our understanding of emerging trends.

Monitor Market Projections: Keep an eye on market forecasts and reports to understand the growth trajectory of IoT and AI. This knowledge helps us anticipate shifts and adapt our learning strategies accordingly.

Experiment With Iot Devices

To truly grasp the concepts surrounding IoT, experimenting with actual devices is vital. By getting hands-on experience, we can better understand how these interconnected devices operate and communicate.

Let’s start with simple projects, like setting up a smart home device or building a DIY IoT sensor. These projects not only teach us the basics but also expose us to real-world challenges and solutions.

As we experiment, we need to think critically about security vulnerabilities. Each device comes with its own set of potential risks—like weak passwords or unpatched software—that we must address. By actively identifying these issues, we can learn to implement better security practices, such as employing Intrusion Detection Systems (IDS) or utilizing machine learning for anomaly detection.

Joining online forums or local maker groups can enhance our learning experience. Sharing our findings and troubleshooting together can lead to deeper insights.

Moreover, collaborating with peers allows us to tackle more complex projects, pushing our understanding further. Ultimately, the more we experiment with IoT devices, the more proficient we become in creating secure, functional solutions that can drive innovation.

Let’s dive in and explore the endless possibilities!

Learn AI Algorithms

Learning AI algorithms opens up a world of possibilities for enhancing our understanding of IoT data analysis. By diving into these algorithms, we can significantly improve how we interpret and utilize data from various IoT devices.

We can focus on the following key areas:

Supervised and Unsupervised Learning: Supervised learning helps us recognize patterns using labeled datasets, while unsupervised learning uncovers hidden insights from unlabeled data.

Anomaly Detection: By employing methods like clustering and classification, we can effectively identify deviations in data, enhancing system security and reliability.

Predictive Maintenance: Utilizing machine learning to analyze historical data lets us predict equipment failures, optimizing maintenance and reducing downtime.

Deep Learning Techniques: With deep neural networks, we capture complex patterns in high-dimensional data, excelling in tasks such as image processing and sequential data analysis.

Collaborate With Peers

Collaborating with peers offers tremendous benefits in our journey to master IoT and AI. When we come together, we can share knowledge, tackle complex problems, and inspire each other to push our limits.

Engaging with a diverse group allows us to gain new perspectives and insights that enrich our understanding of these dynamic fields.

We should actively participate in forums, online communities, and study groups that focus on IoT and AI. These platforms provide opportunities to discuss our ideas, ask questions, and receive constructive feedback.

By working on group projects or challenges, we can apply theoretical concepts practically, which deepens our learning experience.

Additionally, collaborating helps us stay updated with industry trends and best practices. We can learn about the latest tools, technologies, and methodologies from each other, ensuring we’re on the cutting edge of innovation.

Networking with our peers often leads to valuable connections, opening doors for future collaborations or job opportunities.

Ultimately, by fostering a collaborative spirit, we not only enhance our own skills but also contribute to the growth of the entire community.

Together, we can navigate the ever-evolving landscape of IoT and AI more effectively.

Analyze Real-World Case Studies

Building on our collaborative efforts, analyzing real-world case studies can significantly enhance our understanding of IoT and AI applications.

By examining how these technologies are utilized in various sectors, we gain valuable insights that can inform our own projects and initiatives.

Here are four impactful examples we should consider:

IBM Watson in Healthcare: IBM’s AI system provides cancer treatment recommendations, showcasing AI’s potential to improve patient outcomes.

Google DeepMind: This project achieved groundbreaking results in protein folding predictions, demonstrating AI’s capabilities in complex scientific challenges.

Amazon’s Supply Chain Optimization: By leveraging AI for inventory management and pricing strategies, Amazon sets a standard for efficiency in retail.

Banking Sector Chatbots: The implementation of AI-driven customer service chatbots illustrates how financial institutions enhance user experiences and operational efficiency.

Continuously Sharpen Your Skills

To thrive in the rapidly evolving fields of IoT and AI, we must prioritize continuous skill enhancement. Embracing lifelong learning not only keeps us relevant but also boosts our problem-solving capabilities. By building a strong foundation in programming and data analysis, we set ourselves up for success.

Engaging with online courses and tutorials focused on machine learning and IoT basics helps us grasp the essential concepts. Participating in hands-on projects is vital to apply theoretical knowledge practically.

Let’s join forums and communities to exchange ideas and solutions, fostering collaboration and growth. Staying updated with industry trends through publications and webinars ensures we’re aware of the latest advancements.

Experimenting with various IoT devices and AI algorithms deepens our understanding, making us more adaptable to changes in technology. Additionally, collaborating with peers enhances our learning experiences and encourages the sharing of insights.

Frequently Asked Questions

How to Learn AI and Iot?

To learn AI and IoT, we should focus on foundational programming skills, engage in hands-on projects, and actively participate in communities. Staying updated with industry trends will help us enhance our understanding and application of these technologies.

How to Combine AI and Iot?

To combine AI and IoT, we should explore how AI analyzes data from IoT devices. Let’s experiment with various algorithms and collaborate on projects, enhancing our skills while staying updated on emerging trends in this space.

How Can AI Be Used in Iot?

AI enhances IoT by enabling real-time data analysis, improving decision-making. We can leverage AI for predictive maintenance, patient monitoring, and smart transportation, creating efficient, responsive systems that significantly benefit various sectors and our daily lives.

How Can AI Be Used in Iot?

We can use AI in IoT to analyze real-time data, allowing devices to make smart decisions, optimize energy use, enhance security, and improve maintenance. Together, let’s explore these innovations for a more connected future.

Conclusion

In our journey through the realms of IoT and AI, we’ve discovered that building strong programming foundations, engaging in hands-on projects, and collaborating with peers are essential for success. By staying updated on industry trends and analyzing real-world case studies, we’ll continuously sharpen our skills. Let’s embrace these tips and inspire one another as we navigate this dynamic landscape together, unlocking new opportunities and innovations in the exciting world of technology.

Sign up for free courses here. 

Visit Zekatix for more  information.

[neuailabs]

Master Automotive Embedded Systems at NeuAI Labs

Drive success in the automotive industry with our specialized course on designing, developing, and testing embedded systems for vehicles.

[crumblinggothicarchitecture]

re: what the previous anon said about AAVE grammar

ig this is more of a question for the black/african american community but is there anyway to use AAVE terms and grammar respectfully by someone who's not part of the community? I'm not white. I'm not even american, I'm from asia but I wanted to know because it had been so popularised in english-speaking internet i sometimes speak like that unintentionally so I was wondering if that's okay

Hello dear friend, I would suggest maybe asking someone who is within the Black community.

I'm Irish American- so I never really use AAVE, personally. I do, however, just read a lot of linguistic papers- and am currently in a postcolonial studies program wherein I read theories from Black intellectuals often.

I do think there is a difference between Online slang and AAVE; however, I know that it does tend to become interchangeable. Certain words and phrases become popularized through mass media- it is just the happenstance of the digital age. I don't think there is anything wrong with using phrases you find to be useful to your specific expressive needs- so long as it is not used in sarcastic manner or otherwise intentioned to make fun of the phrase. I guess just use it with appreciation for the people and culture from which it comes?

It is an interesting question. I think, as globalization continues to expand, that most people are wondering about the line between cultural appreciation and cultural appropriation.

I cited Glissant in my last post, and I do think Glissant would appreciate the interconnected dialogic of multiple communities making use of each other's linguistic markers. That's what I would surmise, at least, after having read everything he's ever written. To be clear, Glissant was a black Caribbean intellectual- not American- however, his prime contribution to the philosophy of linguistics was concerned with hybridization and cultural exchange. He, ultimately, argued that language is a medium of expression which will always reflect the interconnected nature of humanity. His position was such- because he was a Martinican writer. Martinique- of course- being a past colony of France continues to use French in their everyday lives. In fact, most people of Martinique speak only French- and the French dialect spoken there is creolized. Meaning that the French language there has been modified by the cultural situation and the cosmological structure of the people who use the language. Creole and French now have different vernaculars- within similar syntactical structures. It's really very fascinating to me- how we share and adapt language using it also to construct a cultural reality.

He argues in favor of creolization (or hybridity) because he argues that identity and language is constructed through systems of relation- not isolation. My argument would be inline with this logic. I think that people are innately interconnected- we build meaning, language, thought through relation to others. What is language if not a means to connect with each other? That includes relation to other cultures. So, I don't think it's wrong to say things like "it be like that" with the use of the Habitual "be" or "he funny" as an example of the omitted "be"

Words like "finna" or "lit" or "woke" have all long histories of embedded meaning in AAVE, which is also now part of youth culture and broader internet slang. I think this is just a natural result of our most human impulses- to share and feel a kinship to one another.

If I am wrong- I would welcome a correction. What do you think about the matter?

Also- I don't want to make it seem like Glissant believes all language is interchangeable. That is not the case, but that he does think difference is more constructive when viewed through a lens of solidarity and inter community dialogue. He coined "Tout Monde" meaning- all world, as an explanatory device for his theory that we all construct our reality in relation to each other. Through fluidity and not separation.

[mchiti]

The American black and white thinking is so crazy and the worst part is that it seems like it’s infecting every online space. Like even for minor things like football opinions or music/film reviews you see it. It’s even worse when it’s serious things like what’s happening with Liam. I’m 100% convinced that if Britney Spears were going through her breakdown today, young “progressive” Americans would try to find some problematic thing she said or did to justify bullying her. They like to pretend that they’re better than previous generations but they’re not, they just their cruelty under a progressive veneer.

right? ... just to give you an idea one of my fave korean artists had a minor incident months ago, he fell off an electric scooter by himself (was proceeding pretty slow on the cycle lane and all). he had drank something tho (not much but right enough to exceed) and so had his license revoked and a whole mess followed. now you would expect south korean media to be quite harsh on it because artists there are supposed to be perfect 24/7 (it's ugly but it is what it is) but if you go on certain dominantly american sites (redd*t, ohnoth*ydidnt, any other gossipy-starbiz dedicated forum like that) is full of american lashing their cruelty because "well doesn't matter it was an e-scooter, still ugly, still fucked up, still messed from him, so fuck him, there's no excuse for..." and fuck him fuck him fuck him etc.

like bruh at some point we need to address this toxicity for real and when I say it is embedded in their culture it's because it truly is. USA literally created a bipartisan system, they only have two political parties competing, they divided the whole world into the good side (them + the west) and the bad (ussr + allies) and they keep doing it now (christians vs muslims, west vs east, capitalism vs communism, conservatism vs progress...). it's a very pragmatic culture after all, always has been. you either do good or you do bad, you're either socially acceptable or you're fucked. one single mistake, one single word said wrong and you're fucked for life. this punitive thinking dressed as being progressive and woke... when in fact it sounds pretty fascist to me. extremely fascist.

of course not all americans are like that but in general I don't think usa (and in a minor stance the brits tbh) ever got rid of their inner catholic puritanism tbh. Human beings are complicated and complex and nuanced and deep and sometimes contradictory. they can be beautiful, they can also be terrible, but they are still humans. Cancelling someone over one single word out of place or one single mistake...of course in the case of LP he did way more than that. Of course he had to pay. but what part of me showing some sadness for a young life ended like that means siding with the "oppressor" ? all these big words pronounced and not an once of empathy towards anything or anyone. what world is this really? might work in the individualist capitalist bubble they live in but I'm not into that.

[trendhacking]

Why is C Programming language most Popular for Beginners Programmer?

C is a popular choice for beginner programmers for several reasons:

Foundational Concepts: C teaches essential programming concepts like data types, variables, functions, loops, and control flow. These concepts are fundamental building blocks for many other programming languages.

*Relatively Simple Syntax: C has a relatively simple and straightforward syntax compared to some other languages. This makes it easier for beginners to learn the basics of programming without getting overwhelmed by complex syntax rules.

Direct Hardware Interaction: C provides a level of control over hardware that most higher-level languages don't. This can be beneficial for beginners who want to understand how computers work at a deeper level.

Wide Range of Applications: C is used in various applications, from operating systems and device drivers to embedded systems and game development. Learning C can open doors to various programming fields.

Abundant Learning Resources: C has been around for a long time, and there are many learning resources available, including tutorials, books, and online courses. This makes it easy for beginners to find the help they need when learning the language.