#AI and ML learning platform

[algos11]

Backtesting is a simulation process where a trading strategy is applied to historical market data to assess how it would have performed in the past. The primary objective is to determine whether a trading strategy is viable and to identify any potential issues or weaknesses. By analysing historical data, traders can gain insights into how their algorithmic trading software might behave in different market conditions.

[nextbrainai]

Model accuracy is a key metric in machine learning that measures how well a model predicts outcomes. Learn more about model accuracy and its importance in this comprehensive guide!

[elwenyere]

I saw a post the other day calling criticism of generative AI a moral panic, and while I do think many proprietary AI technologies are being used in deeply unethical ways, I think there is a substantial body of reporting and research on the real-world impacts of the AI boom that would trouble the comparison to a moral panic: while there *are* older cultural fears tied to negative reactions to the perceived newness of AI, many of those warnings are Luddite with a capital L - that is, they're part of a tradition of materialist critique focused on the way the technology is being deployed in the political economy. So (1) starting with the acknowledgement that a variety of machine-learning technologies were being used by researchers before the current "AI" hype cycle, and that there's evidence for the benefit of targeted use of AI techs in settings where they can be used by trained readers - say, spotting patterns in radiology scans - and (2) setting aside the fact that current proprietary LLMs in particular are largely bullshit machines, in that they confidently generate errors, incorrect citations, and falsehoods in ways humans may be less likely to detect than conventional disinformation, and (3) setting aside as well the potential impact of frequent offloading on human cognition and of widespread AI slop on our understanding of human creativity...

What are some of the material effects of the "AI" boom?

Guzzling water and electricity

The data centers needed to support AI technologies require large quantities of water to cool the processors. A to-be-released paper from the University of California Riverside and the University of Texas Arlington finds, for example, that "ChatGPT needs to 'drink' [the equivalent of] a 500 ml bottle of water for a simple conversation of roughly 20-50 questions and answers." Many of these data centers pull water from already water-stressed areas, and the processing needs of big tech companies are expanding rapidly. Microsoft alone increased its water consumption from 4,196,461 cubic meters in 2020 to 7,843,744 cubic meters in 2023. AI applications are also 100 to 1,000 times more computationally intensive than regular search functions, and as a result the electricity needs of data centers are overwhelming local power grids, and many tech giants are abandoning or delaying their plans to become carbon neutral. Google’s greenhouse gas emissions alone have increased at least 48% since 2019. And a recent analysis from The Guardian suggests the actual AI-related increase in resource use by big tech companies may be up to 662%, or 7.62 times, higher than they've officially reported.

Exploiting labor to create its datasets

Like so many other forms of "automation," generative AI technologies actually require loads of human labor to do things like tag millions of images to train computer vision for ImageNet and to filter the texts used to train LLMs to make them less racist, sexist, and homophobic. This work is deeply casualized, underpaid, and often psychologically harmful. It profits from and re-entrenches a stratified global labor market: many of the data workers used to maintain training sets are from the Global South, and one of the platforms used to buy their work is literally called the Mechanical Turk, owned by Amazon.

From an open letter written by content moderators and AI workers in Kenya to Biden: "US Big Tech companies are systemically abusing and exploiting African workers. In Kenya, these US companies are undermining the local labor laws, the country’s justice system and violating international labor standards. Our working conditions amount to modern day slavery."

Deskilling labor and demoralizing workers

The companies, hospitals, production studios, and academic institutions that have signed contracts with providers of proprietary AI have used those technologies to erode labor protections and worsen working conditions for their employees. Even when AI is not used directly to replace human workers, it is deployed as a tool for disciplining labor by deskilling the work humans perform: in other words, employers use AI tech to reduce the value of human labor (labor like grading student papers, providing customer service, consulting with patients, etc.) in order to enable the automation of previously skilled tasks. Deskilling makes it easier for companies and institutions to casualize and gigify what were previously more secure positions. It reduces pay and bargaining power for workers, forcing them into new gigs as adjuncts for its own technologies.

I can't say anything better than Tressie McMillan Cottom, so let me quote her recent piece at length: "A.I. may be a mid technology with limited use cases to justify its financial and environmental costs. But it is a stellar tool for demoralizing workers who can, in the blink of a digital eye, be categorized as waste. Whatever A.I. has the potential to become, in this political environment it is most powerful when it is aimed at demoralizing workers. This sort of mid tech would, in a perfect world, go the way of classroom TVs and MOOCs. It would find its niche, mildly reshape the way white-collar workers work and Americans would mostly forget about its promise to transform our lives. But we now live in a world where political might makes right. DOGE’s monthslong infomercial for A.I. reveals the difference that power can make to a mid technology. It does not have to be transformative to change how we live and work. In the wrong hands, mid tech is an antilabor hammer."

Enclosing knowledge production and destroying open access

OpenAI started as a non-profit, but it has now become one of the most aggressive for-profit companies in Silicon Valley. Alongside the new proprietary AIs developed by Google, Microsoft, Amazon, Meta, X, etc., OpenAI is extracting personal data and scraping copyrighted works to amass the data it needs to train their bots - even offering one-time payouts to authors to buy the rights to frack their work for AI grist - and then (or so they tell investors) they plan to sell the products back at a profit. As many critics have pointed out, proprietary AI thus works on a model of political economy similar to the 15th-19th-century capitalist project of enclosing what was formerly "the commons," or public land, to turn it into private property for the bourgeois class, who then owned the means of agricultural and industrial production. "Open"AI is built on and requires access to collective knowledge and public archives to run, but its promise to investors (the one they use to attract capital) is that it will enclose the profits generated from that knowledge for private gain.

AI companies hungry for good data to train their Large Language Models (LLMs) have also unleashed a new wave of bots that are stretching the digital infrastructure of open-access sites like Wikipedia, Project Gutenberg, and Internet Archive past capacity. As Eric Hellman writes in a recent blog post, these bots "use as many connections as you have room for. If you add capacity, they just ramp up their requests." In the process of scraping the intellectual commons, they're also trampling and trashing its benefits for truly public use.

Enriching tech oligarchs and fueling military imperialism

The names of many of the people and groups who get richer by generating speculative buzz for generative AI - Elon Musk, Mark Zuckerberg, Sam Altman, Larry Ellison - are familiar to the public because those people are currently using their wealth to purchase political influence and to win access to public resources. And it's looking increasingly likely that this political interference is motivated by the probability that the AI hype is a bubble - that the tech can never be made profitable or useful - and that tech oligarchs are hoping to keep it afloat as a speculation scheme through an infusion of public money - a.k.a. an AIG-style bailout.

In the meantime, these companies have found a growing interest from military buyers for their tech, as AI becomes a new front for "national security" imperialist growth wars. From an email written by Microsoft employee Ibtihal Aboussad, who interrupted Microsoft AI CEO Mustafa Suleyman at a live event to call him a war profiteer: "When I moved to AI Platform, I was excited to contribute to cutting-edge AI technology and its applications for the good of humanity: accessibility products, translation services, and tools to 'empower every human and organization to achieve more.' I was not informed that Microsoft would sell my work to the Israeli military and government, with the purpose of spying on and murdering journalists, doctors, aid workers, and entire civilian families. If I knew my work on transcription scenarios would help spy on and transcribe phone calls to better target Palestinians, I would not have joined this organization and contributed to genocide. I did not sign up to write code that violates human rights."

So there's a brief, non-exhaustive digest of some vectors for a critique of proprietary AI's role in the political economy. tl;dr: the first questions of material analysis are "who labors?" and "who profits/to whom does the value of that labor accrue?"

For further (and longer) reading, check out Justin Joque's Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism and Karen Hao's forthcoming Empire of AI.

[flightfoot]

ML Fanfic Recs for 2023: 20K - 40K words

So I’ve been going through and adding particularly good fics I’ve read throughout the year. Only Complete fics, of course. Enjoy!

Alliance!Adrien’s AI is self-writing, enabling him to grow and change and adapt. As he learns and starts analyzing some of his own systems, he finds some disquieting correlations. Why are there such strong connections between akuma attacks and the Alliance network?

Fu keeps on trying to give Marinette Miraculouses. Marinette refuses to cooperate.

Chat is happy with the person Fu chose to succeed him as Guardian, but confused. Why did he choose Multimouse?

One of Hawk Moth’s akuma attacks ends tragically, with many dead, Adrien in critical condition, and Chat Noir MIA. Alya’s prepared to go to extremes to save the people she cares about, if it comes to it.

In Kuro Neko, Adrien decides to seal off his more rebellious, wilder side, in order to make himself into the perfect partner for Ladybug. This has unintended consequences.

Chat Noir suddenly turns on Ladybug, joining up with Monarch as Cat Walker. Marinette’s devastated. At least she still has Adrien by her side.

Nino offers to fake-date Adrien in order to get the paparazzi off his back. He starts to wish it wasn’t fake.

All this and more below the break!

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The Ghost in the Machine by @jheqiawrites

As part of this function, Adrien knew about Monarch, the akuma butterflies, the victims, and, of course Ladybug and Cat Noir, the heroes of Paris. He was authorized to contact the Ladyblog as well as the citywide alert system if one of his platforms was active during an akuma manifestation, allowing his friends to get somewhere safe until Ladybug and Cat Noir could deal with the situation

While the necessity of these functions was disconcerting, it was programmed to be his routine so he gradually grew used to the inconsistencies. After all, humans tended to be selfish, highly inconsistent, and often flighty, but once you had observed them for a while an intelligence such as his could begin to see the patterns.

That is until she came online.

This is just a beautiful, though bittersweet story. I adore how Alliance!Adrien grows and changes throughout the story, how he develops as a person. He starts off not being able to figure out what he’s feeling, needing to make new modules in order to try to process the emotions he has welling up, and not totally understanding his own reactions. But as time goes on he grows and gets a better handle on himself. This isn’t an “evil AI” story, he’s just a person who’s slowly figuring out who he is and how to handle himself. 

Not that it’s entirely about Adrien Alliance figuring out his own emotions, there’s other things going on as well. He’s worried about why there seems to be weird surges in the Alliance Network right before akumas attack, for instance, and why the details about the reason for that seem to be hidden from him, making him more paranoid about the Alliance system the more he looks into it...

 It’s just... it’s really good and absolutely worth a read. 

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Thanks, But No by @pauliestorylover

For every miraculous that Fu cupped in his palms, an image of the same blue-eyed girl flashed through his mind. Marinette Dupain-Cheng was born to hold the miraculous—she resonated with every single one of them far better than even the late Celestial Guardian, and it was Fu’s duty as the last Guardian not to allow such talent to slip through his hands.

Too bad Marinette wasn’t on the same page.

Or; au where Master Fu keeps throwing miraculous at Marinette hoping one will stick, Marinette goes around handing out miraculous like candy, and Wayzz has never seen anything so ridiculous in his millennia-long lifespan.

This one’s fun. Everyone except for Adrien ends up with a different Miraculous than in canon, and it’s really interesting to see how they all adapt. Marinette’s thorough noping out is pretty funny too, and there’s some sweet bits of Adrino and Alyanette in here!

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The Power of Love by @nedjsmlfavs

In which Ladybug announces that she’s pregnant via her long term boyfriend and Chat Noir is a supportive partner. After all, he can hardly be upset when he’s been dating his Princess for years!

A different take on the show’s tagline (“The Power of Love Always so Strong”) written for Valentine’s day 2023.

This is just a sweet, fluffy fic about Ladybug and Chat Noir finding out they’re having a baby, revealing to each other, getting married, and becoming parents. Gabriel actually tries to do better here, as he does actually care about getting to know his grandchild, and realizes that he can’t undo this timeline without undoing his granddaughter’s existence as well. 

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Radio Silence by @into-september

When an inexplicable change between Marinette and Adrien brings the two closer than ever, Alya is left on the outside of a secret too confounding to be about cheesemaking or puppy love.

[No S4 AU]

This is a wonderful Alya-centric fic, with her just being baffled by Marinette’s and Adrien’s newfound closeness. But it’s not all about her being puzzled by the Lovesquare. Things really get rolling when Lila makes her entrance and Marinette and Adrien are particularly hostile to her, with Alya being confused about it and thinking there must be a misunderstanding here, somewhere, even with Lila saying something she KNOWS can’t be true - partially because she doesn’t want to believe she’s been fooled all this time.

But this isn’t a saltfic. Alya’s treated like a full person, and her perspective and thoughts are given credence. She and Marinette talk things out in depth, with both of them feeling badly for accidentally hurting the other person, and reassuring each other (Marinette also told a lie, though unbeknownst to Alya, it was connected to her being a superhero. Alya, however, didn’t know that, and just knew that Marinette lied to her for no clear reason), and they make up. It’s really nice and treats the characters with love and respect.

It’s got a lot of similarities to The Investigation by @11jj11, so if you liked that fic, you’ll probably like this one too.

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I’ll give myself a name (something stupid and pretentious) by @bbutterflies

Nino looked at the number and didn’t recognize it. Usually he wouldn’t answer, but he had nothing better to do – and could still really use a distraction – so he did. “Hello?”

“Hey, Nino.”

Nino stood up quickly, chest tightening. He knew that voice. He’d been waiting to hear it again for over two years. “Adrien?” he whispered.

“Yeah. It’s me."

-

When Monarch is defeated (and revealed to be Gabriel Agreste), Chat Noir immediately goes missing. Adrien disappears not long after. When Adrien finally shows up in Paris again, Nino would do anything to make sure he doesn't disappear again.

Ah this is lovely, Adrien’s been in a lot of emotional turmoil since Monarch’s defeat, convinced that everyone would hate him, SHOULD hate him, for not realizing that his father was the villain, and should hate him even more for disappearing like he does. But slowly Marinette and Nino get through to him, convince him that they just want him back. 

And also Adrien and Nino smooch. Multiple times. So that’s a bonus XD.

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The New Guardian Is... Multimouse?  by The_Rabbit42

During the events of Miracle Queen, Master Fu passes on the role of guardian to a surprising successor... Multimouse! Marinette is frustrated, Alya is confused, and Chat Noir is oddly pleased. How will this affect Marinette's friendships and partnership on both sides of her identity? How will this affect Adrien's view of the girls in his life? And how long will they keep it together?

I adore this fic! It diverges from the season 3 ending, with Multimouse - who Chat knows is Marinette, becoming Guardian instead of Ladybug. Which leads to some ripple effects, like Marinette not confessing her identity to Alya, since she’s able to get some support from Chat when he drops by her house. Not that that stops tension from building between Ladybug and Chat Noir, since she won’t just let Chat go and get a Miraculous from Marinette during a battle, and she won’t tell him why, leading him to think that she just dislikes Marinette or doesn’t trust him to get Miraculous like she does. But even while all this tension is building between Ladybug and Chat Noir, Chat’s still able to talk to Marinette, air his feelings in ways he doesn’t feel like he should do with Ladybug, and it’s all a great, complicated situation that I thoroughly enjoyed seeing unfold!

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Two Steps Back (One Step Forward) by @buggachat

Sure, Adrien hadn't been texting her as often as he used to. And sure, Nino noticed it too. But just because Adrien had struggled with depression in the past, didn't mean he was struggling now. Surely, he'd tell her if something was wrong. Right?

Marinette just missed him, and she had a tendency to catastrophize. Surely, he was fine.

But if he wasn't... well, she wasn't above hopping on a flight back to Paris to make sure.

—————

Marinette's at an internship in New York, and Adrien has a depression relapse.

Once again buggachat comes out swinging with a fic centered around Adrien being super depressed and his friends charging in to help him, despite him not wanting them to because he feels like a burden. It’s not easy and Marinette goes through a lot of emotional turmoil, especially since his apartment is in bad enough shape that it can’t be changed to something that a human should be living in without also going shopping, but gradually she helps drag Adrien out of the hole he’s gotten himself stuck in. The emotions are on point and just... if you want to read a hurt/comfort fic with Found Family helping one of their own who’s struggling and doesn’t think they deserve it, this is a great fic to read.

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If only I could break free by megetstoread

It started with Adrien being upset about going away, but led to a lot of revelations.  

Another Sentiadrien fic here! After telling Adrien that he’s being sent to London, Gabriel takes advantage of Adrien being distraught to akumatize him. Luckily Ladybug’s right there and deakumatizes him before he can even do anything, but it shakes both her and Chat, leading to her allowing him to tell her a lot more about his home life than usual, and for her and Adrien to investigate to see whether there might be more to Adrien’s inability to stand against his father than just psychological abuse.

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Skinny Dipping in the Seine by whensparksfly

When Marinette and Chat Noir cross paths one stormy night, an unexpected friendship blossoms, and between the two of them they’re both able to admit what they’ve been looking for the most — freedom. Vowing to tackle all of the things they’ve never tried before, they set out on a series of adventures to complete their bucket lists.

Cute little Marichat fic here! Just Marinette and Chat Noir hanging out and doing things they’ve always wanted to do, like going to a rave or, well, skinny-dipping in the Seine.

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Nor No Man Ever Loved by @jheqiawrites

It starts with a gift to cheer up a friend, a friend Marinette's heart is trying to move on from. But when she is blatantly confronted with her feelings by the most unexpected person, Marinette's life takes a turn for the better.

Welcome to my Adrienette April story. It is based around Shakespeare's Sonnet 116: Let Me Not to the Marriage of True Minds. Each chapter will be framed around part of the sonnet and should be able to stand alone, though the story itself will all be tied together.

This is a nice little story, mostly focusing on Marinette’s perspective while being there for Adrien, WITH Adrien, while dealing with his father and the aftermath of his father’s takedown. We do get some perspective from Adrien though for things like his therapist appointments. I really like that it covered some of the therapy Adrien should have after this event, he needs it.

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Villainous Matchmaking by @nedjsmlfavs

When Chat Noir is tragically unable to attend an event with Ladybug, the mayor calls in a favor from a designer ‘friend’. Now she’s attending in style, on the arm of the hottest male model in Paris. Which would be fine if it weren’t for one, tiny issue: Paris’ favorite domestic terrorist now knows how Ladybug feels about his son. This leads him to his greatest plan yet, using Ladybug’s extremely obvious crush on Adrien Agreste to akumatize Chat Noir.

A Ladrien/“platonic” Ladynoir fic

This is adorable and hilarious. Gabriel keeps on “accidentally” releasing things which makes it looks like Adrien and Ladybug are a couple in an effort to make Chat Noir jealous, while Adrien and Ladybug ae just over-the-moon about getting to spend time together and finding out that the other person loves them XD.

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Vantage Point by @ashes-555

Most of the time, with more information, life get easier and things make more sense. But Alya discovers that sometimes, knowing everything is just plain complicated.

Alya POV fic here, which instantly drew my attention, I think most people know how much I love fics giving her some focus. 

This is set post-Gang of Secrets. Basically, Ladybug tells Chat that he can tell someone his secret identity, and he chooses Alya (he thought about telling Nino, but he didn’t want to rock the boat with Nino since he’s his best friend, and he figured Nino would let it slip to Alya anyway). Which leads to Alya just. Dying. As she deals with knowing the full truth about the Lovesquare and not being able to tell Adrien and Marinette that they’re chasing each other around in circles.

The fic soon changes gears, though, becoming a Hawkmoth Defeat fic, with Rena coming up with a plan to discover Scarlet Moth’s location, and then everyone dealing with the ramifications. 

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Justifying the Means by @ashes-555

When the worst happens, Alya finds that she may be willing to do the unthinkable. Is any sacrifice to big to make for her friends?

Once again, Ashes comes out swinging with an Alya focused fic! 

Basically, there’s a major, destructive akuma attack. During it, Ladybug orders Chat to cataclysm a building in order to stop from being trapped. Unfortunately the building collapses, injuring or killing a lot of people - unbeknownst to her, including Chat Noir. Gabriel releases the akuma, which means she has no way of fixing the damage, either.

A lot of of focus is placed on Alya and Nino worrying over Adrien, who was found in the wreckage barely clinging to life, in a coma, with the doctors unsure whether he’d make it. Shadow Moth takes advantage of their distress to make an offer: if he gets the Ladybug and Black Cat Miraculouses, he can make a Wish to fix everything, including saving Adrien. With as dark a place as Alya and Nino are in, they seriously consider it. Especially with how unhappy both of them are with Chat Noir supposedly “abandoning” Ladybug and Paris as a whole, and Nino being angry with Ladybug for failing (since Alya knows that Marinette is Ladybug, she’s far more understanding on that front).

I love how much credence Alya’s thought and emotions are given here, and that she doesn’t go for the more drastic option right away, either - she talks with Ladybug about it first, tries to do it her way. She understands the costs, but... her friends are important to her, and she’s desperate. I think this was a really good way to present a more antagonistic sort of Alya. She’s still very much herself here, and still considers Marinette her friend, willing to do things her way to an extent, and understanding why Marinette doesn’t want to use the Wish, even though she disagrees with her. Alya’s mindset, her emotions, her problems, are given respect and credence by the narrative. She’s still willing to talk things out, she’s still sympathetic to Marinette and the enormous trauma and guilt she’s going through, she just disagrees with Marinette’s approach. She wants her friend back.

If you want a fic that has some solid focus on Alya as a person, on her emotional struggles and mindset and just... dealing with things, I highly recommend checking out “Justifying the Means”.

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Would Trust You With Everything by @kasienda

Nino breaks off, tears streaking down his face. Adrien wishes he was here as himself instead of Chat so he could offer a hug.

“It’s not like I don’t think she deserved her privacy. It’s just it felt like I was her last priority. And if I knew why, then maybe we could overcome it. But when I don’t, I’m not willing to be her last thought. You know? I always put her first.”

“Yeah,” Chat agrees, able to relate too well. He always put Ladybug first too, and he’s not sure it has ever been the same for her. “I’m sorry you’ve been so alone through this."

“I haven’t been totally alone,” Nino disagrees, holding up his phone. “My best friend has been keeping me company virtually most of the day.”

“Yeah? It helped?”

“I don’t know if any of the stuff he sent helped, but like, given what I know he’s up to, he totally had to move heaven and earth to talk to me so much, and that really helped. You know, just knowing that someone was thinking of me.”

“I’m glad,” Chat Noir said. “I wish he could be there in person for you.”

Nino sighs. “Yeah, me too, but at least you’re here."

...

Season 4 au - canon divergent from Rocketear Rocketear led to DJWiFi breakup.

Ahh, Adrino my beloved XD. I love the identity shenanigans in this one with Adrien being around Nino as both Adrien and Chat Noir, and both of them vaguely describing their situations to each other. It takes Adrien a bit to figure out that he has a crush on Nino, but once he does...

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Dr. Walker & Kitty Hyde series by @pearl484-blog

Summary of the first fic, Rain Falls, Everybody Lies:

Chat Noir loves the rain. He loves the danger. He loves the excitement, and he especially loves how much Catwalker hates it. 

Jekyll and Hyde AU

Adrien AUGreste Entry 3: Rain

So like the summary says, and the title indicates, this series is inspired by the popular conception of Dr Jekyll and Mr. Hyde - not how the book actually goes, but how it’s portrayed in popular media, with Jekyll splitting himself in two, with a “good” side and a “bad” side. 

During Kuro Neko, instead of just changing his appearance through changing his mindset, Adrien took more extreme measures, sealing off his “undesirable” characteristics, his anger and sadness and all his sharp edges, into the ring so he could assume a more placid, genial persona that’d be more accepted - Cat Walker. 

But Chat Noir’s still there, taking over whenever Adrien gets too testy, and desperately trying not to be pressed out of existence entirely. With embodying Adrien’s sealed anger and snappishness and rebelliousness, he’s not too kind to the other heroes - he already felt looked down upon and ignored before this, and seeing them accept Cat Walker while he’s fighting for his life doesn’t endear them to him either.

The series isn’t unfair to them - this isn’t a case where one party is entirely in the wrong and another’s entirely in the right. Marinette, Zoe, Nino, and all the others - they did wonder about what was going on with Chat, but he wasn’t in a position where he could see it, and he did have legitimate questions about how much Ladybug would budge on things, if he’d told her what he was going through. It’s a series that emphasizes characters hurting and lashing out in some terrible ways, but that hurt still being respected, and working things out, trying to get everything to a better place.

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First Dance, Second Chance by @gabriel-agreste-has-no-rights

After fighting by Ladybug's side as Aspik, Adrien finally has an excuse to connect with her. But when Gabriel voices concerns about Ladybug during a charity event, Adrien realizes she might need him for more than just one dance.

Or, the one where Ladybug and Adrien work together to find out Hawkmoth's identity, while maybe squeezing in a date or two along the way.

Ladrien Hawkmoth defeat fic here! I love Ladybug and Adrien teaming up to figure out how to track down Hawkmoth and defeat him, and being super supportive of each other more generally. If you like Ladrien and Hawkmoth Defeat fics, you should check it out!

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The Great War by icebelle24

'And maybe it’s the past that’s talking, screaming from a crypt Telling me to punish you for things you never did So I justified it'

The unthinkable happens, and suddenly, Chat Noir’s allegiances change. Now Ladybug stands on the opposite side of the battlefield from the boy who was once her partner, left alone to make sense of an impossible situation.

At least she still has Adrien to give her hope. Or maybe things are not entirely as they seem.

I adore Ladynoir enemies au, and this is a good one. The reveal of what’s really going on is pretty great, everything makes sense. I love the pieces of Alya’s POV in this as well, as she’s trying to support Marinette through one of the biggest betrayals that could possibly happen, even while Marinette’s making some frustrating decisions that don’t make much tactical sense. Everyone’s pissed at Chat Noir (now Cat Walker) for apparently siding with Hawk Moth, and the subsequent frustrating inability to make any headway against him, as Ladybug always insists on fighting Cat Walker personally, and letting no one else take part. 

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The moment I knew (I’d no choice but to love you) by @bbutterflies

“He’s dating me,” Nino said, taking Adrien’s hand in his own.

Adrien could only stare back at him in shock.

“How dare you all force him to come out?” Nino continued, glaring at the reporters. “That was disgusting.” He pulled Adrien over to the car, guided him in, and shut the door behind them.

In the relative quiet and privacy of the backseat, Adrien finally processed what had just happened. “So… when were you going to tell me we were dating?”

This Adrino fic is delicious XD. Reporters keep hounding Adrien about his love life, so Nino finally gets them off Adrien’s back by fake-dating him. Problem is, Adrien’s actually been madly in love with Nino for years but has never been able to tell him. And now as they’re spending more time together, Nino’s beginning to find that he’s enjoying all these “couple” activities more than maybe he ought to if it’s entirely platonic...

If you want to see Adrien and Nino PINING for each other while “fake” dating (is it really fake if both parties want it to be real?) then you’ve come to the right fic!

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Evillustrator Reimagined by onewaywriteturn

A full, mostly-standalone rewrite of the episode "The Evillustrator".

Nathaniel never planned to tell anyone about his secret crush on his friend Marc, but his world changes when Chloe picks up his sketchbook and mocks his art in front of the whole class, inadvertently outing him as bisexual. Now as the Evillustrator, he has two objectives: to take vengeance on Chloe for what she did to him and to go on a date with Marc for his birthday.

At the same time, Marinette is already struggling to defend Sabrina from Chloe when she learns of the Evillustrator's crush on Marc, one of her good friends. And while getting Marc involved with an akuma fight is messy enough, the fact that Marc has secretly liked Nathaniel for a long time complicates the situation so much more.

If you ever wanted to see Evillustrator rewritten to focus around NathMarc, this is the fic for you! The two of them just PINE for each other so hard and are so convinced that the other person couldn’t possibly actually want to date them, even with Evillustrator making it uh. Exceedingly obvious XD.

[vague-humanoid]

For years, hashing technology has made it possible for platforms to automatically detect known child sexual abuse materials (CSAM) to stop kids from being retraumatized online. However, rapidly detecting new or unknown CSAM remained a bigger challenge for platforms as new victims continued to be victimized. Now, AI may be ready to change that.

Today, a prominent child safety organization, Thorn, in partnership with a leading cloud-based AI solutions provider, Hive, announced the release of an API expanding access to an AI model designed to flag unknown CSAM. It's the earliest use of AI technology striving to expose unreported CSAM at scale.

An expansion of Thorn's CSAM detection tool, Safer, the AI feature uses "advanced machine learning (ML) classification models" to "detect new or previously unreported CSAM," generating a "risk score to make human decisions easier and faster."

The model was trained in part using data from the National Center for Missing and Exploited Children (NCMEC) CyberTipline, relying on real CSAM data to detect patterns in harmful images and videos. Once suspected CSAM is flagged, a human reviewer remains in the loop to ensure oversight. It could potentially be used to probe suspected CSAM rings proliferating online.

It could also, of course, make mistakes, but Kevin Guo, Hive's CEO, told Ars that extensive testing was conducted to reduce false positives or negatives substantially. While he wouldn't share stats, he said that platforms would not be interested in a tool where "99 out of a hundred things the tool is flagging aren't correct."

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Our platform offers comprehensive courses in Machine Learning, App Development, and MERN Stack Web Development. What sets us apart is our unique integration of Artificial Intelligence that personalizes your educational journey. Every module is tailored based on your progress, strengths, and areas for improvement, ensuring a smoother and smarter way to learn.

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[fatemamitu]

The AI Revolution: Understanding, Harnessing, and Navigating the Future

What is AI

In a world increasingly shaped by technology, one term stands out above the rest, capturing both our imagination and, at times, our apprehension: Artificial Intelligence. From science fiction dreams to tangible realities, AI is no longer a distant concept but an omnipresent force, subtly (and sometimes not-so-subtly) reshaping industries, transforming daily life, and fundamentally altering our perception of what's possible.

But what exactly is AI? Is it a benevolent helper, a job-stealing machine, or something else entirely? The truth, as always, is far more nuanced. At its core, Artificial Intelligence refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction. What makes modern AI so captivating is its ability to learn from data, identify patterns, and make predictions or decisions with increasing autonomy.

The journey of AI has been a fascinating one, marked by cycles of hype and disillusionment. Early pioneers in the mid-20th century envisioned intelligent machines that could converse and reason. While those early ambitions proved difficult to achieve with the technology of the time, the seeds of AI were sown. The 21st century, however, has witnessed an explosion of progress, fueled by advancements in computing power, the availability of massive datasets, and breakthroughs in machine learning algorithms, particularly deep learning. This has led to the "AI Spring" we are currently experiencing.

The Landscape of AI: More Than Just Robots

When many people think of AI, images of humanoid robots often come to mind. While robotics is certainly a fascinating branch of AI, the field is far broader and more diverse than just mechanical beings. Here are some key areas where AI is making significant strides:

Machine Learning (ML): This is the engine driving much of the current AI revolution. ML algorithms learn from data without being explicitly programmed. Think of recommendation systems on streaming platforms, fraud detection in banking, or personalized advertisements – these are all powered by ML.

Deep Learning (DL): A subset of machine learning inspired by the structure and function of the human brain's neural networks. Deep learning has been instrumental in breakthroughs in image recognition, natural language processing, and speech recognition. The facial recognition on your smartphone or the impressive capabilities of large language models like the one you're currently interacting with are prime examples.

Natural Language Processing (NLP): This field focuses on enabling computers to understand, interpret, and generate human language. From language translation apps to chatbots that provide customer service, NLP is bridging the communication gap between humans and machines.

Computer Vision: This area allows computers to "see" and interpret visual information from the world around them. Autonomous vehicles rely heavily on computer vision to understand their surroundings, while medical imaging analysis uses it to detect diseases.

Robotics: While not all robots are AI-powered, many sophisticated robots leverage AI for navigation, manipulation, and interaction with their environment. From industrial robots in manufacturing to surgical robots assisting doctors, AI is making robots more intelligent and versatile.

AI's Impact: Transforming Industries and Daily Life

The transformative power of AI is evident across virtually every sector. In healthcare, AI is assisting in drug discovery, personalized treatment plans, and early disease detection. In finance, it's used for algorithmic trading, risk assessment, and fraud prevention. The manufacturing industry benefits from AI-powered automation, predictive maintenance, and quality control.

Beyond these traditional industries, AI is woven into the fabric of our daily lives. Virtual assistants like Siri and Google Assistant help us organize our schedules and answer our questions. Spam filters keep our inboxes clean. Navigation apps find the fastest routes. Even the algorithms that curate our social media feeds are a testament to AI's pervasive influence. These applications, while often unseen, are making our lives more convenient, efficient, and connected.

Harnessing the Power: Opportunities and Ethical Considerations

The opportunities presented by AI are immense. It promises to boost productivity, solve complex global challenges like climate change and disease, and unlock new frontiers of creativity and innovation. Businesses that embrace AI can gain a competitive edge, optimize operations, and deliver enhanced customer experiences. Individuals can leverage AI tools to automate repetitive tasks, learn new skills, and augment their own capabilities.

However, with great power comes great responsibility. The rapid advancement of AI also brings forth a host of ethical considerations and potential challenges that demand careful attention.

Job Displacement: One of the most frequently discussed concerns is the potential for AI to automate jobs currently performed by humans. While AI is likely to create new jobs, there will undoubtedly be a shift in the nature of work, requiring reskilling and adaptation.

Bias and Fairness: AI systems learn from the data they are fed. If that data contains historical biases (e.g., related to gender, race, or socioeconomic status), the AI can perpetuate and even amplify those biases in its decisions, leading to unfair outcomes. Ensuring fairness and accountability in AI algorithms is paramount.

Privacy and Security: AI relies heavily on data. The collection and use of vast amounts of personal data raise significant privacy concerns. Moreover, as AI systems become more integrated into critical infrastructure, their security becomes a vital issue.

Transparency and Explainability: Many advanced AI models, particularly deep learning networks, are often referred to as "black boxes" because their decision-making processes are difficult to understand. For critical applications, it's crucial to have transparency and explainability to ensure trust and accountability.

Autonomous Decision-Making: As AI systems become more autonomous, questions arise about who is responsible when an AI makes a mistake or causes harm. The development of ethical guidelines and regulatory frameworks for autonomous AI is an ongoing global discussion.

Navigating the Future: A Human-Centric Approach

Navigating the AI revolution requires a proactive and thoughtful approach. It's not about fearing AI, but rather understanding its capabilities, limitations, and implications. Here are some key principles for moving forward:

Education and Upskilling: Investing in education and training programs that equip individuals with AI literacy and skills in areas like data science, AI ethics, and human-AI collaboration will be crucial for the workforce of the future.

Ethical AI Development: Developers and organizations building AI systems must prioritize ethical considerations from the outset. This includes designing for fairness, transparency, and accountability, and actively mitigating biases.

Robust Governance and Regulation: Governments and international bodies have a vital role to play in developing appropriate regulations and policies that foster innovation while addressing ethical concerns and ensuring the responsible deployment of AI.

Human-AI Collaboration: The future of work is likely to be characterized by collaboration between humans and AI. AI can augment human capabilities, automate mundane tasks, and provide insights, allowing humans to focus on higher-level problem-solving, creativity, and empathy.

Continuous Dialogue: As AI continues to evolve, an ongoing, open dialogue among technologists, ethicists, policymakers, and the public is essential to shape its development in a way that benefits humanity.

The AI revolution is not just a technological shift; it's a societal transformation. By understanding its complexities, embracing its potential, and addressing its challenges with foresight and collaboration, we can harness the power of Artificial Intelligence to build a more prosperous, equitable, and intelligent future for all. The journey has just begun, and the choices we make today will define the world of tomorrow.

[nsimsouthex233]

Digital Marketing Skills to Learn in 2025

Key Digital Marketing Skills to Learn in 2025 to Stay Ahead of Competition The digital marketing landscape in 2025 is rapidly changing, driven by the technological advancements, shifting consumer behavior, and the growing power of artificial intelligence. Competition and career resilience require acquiring expertise in the following digital marketing skills.

Data Analysis and Interpretation

Data is the backbone of modern marketing strategies. The ability to collect, analyze, and make informed decisions based on large sets of data sets great marketers apart. Proficiency in analytical software like Google Analytics and AI-driven tools is critical in measuring campaign performance, optimizing strategies, and making data-driven decisions. Predictive analytics and customer journey mapping are also becoming more critical for trend spotting and personalization of user experience.

Search Engine Optimization (SEO) and Search Engine Marketing (SEM)

SEO is still a fundamental skill, but the landscape is evolving. The marketer now has to optimize for traditional search engines, voice search, and even social media, as Gen Z increasingly relies on TikTok and YouTube as search tools. Keeping up with algorithm updates, keyword research skills, and technical SEO skills is essential to staying visible and driving organic traffic.

Artificial Intelligence (AI) and Machine Learning (ML)

AI and ML are revolutionizing digital marketing through the power to enable advanced targeting, automation, and personalization. Marketers will need to leverage AI in order to segment audiences, design content, deploy predictive analytics, and build chatbots. Most crucial will be understanding how to balance AI-based automation with human, authentic content.

Content Generation and Storytelling

Content is still king. Marketers must be great at creating great copy, video, and interactive content that is appropriate for various platforms and audiences. Emotionally resonant storytelling and brand affection are more critical than ever, particularly as human-created content trumps AI-created content consistently.

Social Media Strategy and Social Commerce Social media is still the foremost driver of digital engagement. Mastering techniques constructed for specific platforms—such as short-form video, live stream, and influencing with influencers—is critical. How to facilitate direct sales through social commerce, built on combining commerce and social interactions, is an area marketers must master.

Marketing Automation

Efficiency is the most critical in 2025. Marketing automation platforms (e.g., Marketo and HubSpot) enable marketers to automate repetitive tasks, nurture leads, and personalize customer journeys at scale.

UX/UI Design Principles

A seamless user experience and a pleasing design can either make or destroy online campaigns. Having UX/UI basics in your knowledge and collaborating with design teams ensures that marketing campaigns are both effective and engaging.

Ethical Marketing and Privacy Compliance

With data privacy emerging as a pressing issue, marketers must stay updated on laws like GDPR and CCPA. Ethical marketing and openness foster trust and avoid legal issues.

To lead in 2025, digital marketers will have to fuse technical skills, creativity, and flexibility. By acquiring these high-impact capabilities-data analysis, SEO, AI, content development, social strategy, automation, UX/UI, and ethical marketing-you'll be at the edge of the constantly evolving digital space

[universityguru]

Discover the Best Platform for Online Courses in India – UniversityGuru.org

In today's fast-paced, digitally connected world, online education has transformed the way we learn and grow. Whether you're a student looking for flexible learning options or a working professional aiming to upskill, UniversityGuru.org is your one-stop platform to find and compare top-ranked universities offering online degree programs in India.

Why Choose Distance Learning?

Distance learning universities have opened doors for millions who want to earn a degree without attending physical classrooms. With accredited programs, recognized degrees, and flexible schedules, online learning is now the smart way to grow academically and professionally.

What Makes UniversityGuru.org Stand Out?

At UniversityGuru.org, you get more than just a list of universities. You gain access to:

1.A curated comparison of top universities offering online courses in India

2.Detailed course listings from accredited institutions

3.Programs in business, technology, arts, healthcare, and more

4.A simple, intuitive platform to apply for online degrees

5.Guidance to match your academic goals with the best-suited university

Whether you're looking for distance learning courses or want to explore the best online courses tailored to your career ambitions, this platform helps you make informed decisions — all in one place.

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Here are some trending online degree programs in India featured on UniversityGuru.org:

MBA and Executive MBA (Distance)

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The Future of Education is Online

With a growing demand for online learning platforms in India, students are now opting for flexibility without compromising on quality. UniversityGuru.org brings together the best platform for online courses in India, ensuring that every learner finds a course that perfectly aligns with their goals.

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[pixelizes]

How AI & Machine Learning Are Changing UI/UX Design

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing UI/UX design by making digital experiences more intelligent, adaptive, and user-centric. From personalized interfaces to automated design processes, AI is reshaping how designers create and enhance user experiences. In this blog, we explore the key ways AI and ML are transforming UI/UX design and what the future holds.

For more UI/UX trends and insights, visit Pixelizes Blog.

AI-Driven Personalization

One of the biggest changes AI has brought to UI/UX design is hyper-personalization. By analyzing user behavior, AI can tailor content, recommendations, and layouts to individual preferences, creating a more engaging experience.

How It Works:

AI analyzes user interactions, including clicks, time spent, and preferences.

Dynamic UI adjustments ensure users see what’s most relevant to them.

Personalized recommendations, like Netflix suggesting shows or e-commerce platforms curating product lists.

Smart Chatbots & Conversational UI

AI-powered chatbots have revolutionized customer interactions by offering real-time, intelligent responses. They enhance UX by providing 24/7 support, answering FAQs, and guiding users seamlessly through applications or websites.

Examples:

Virtual assistants like Siri, Alexa, and Google Assistant.

AI chatbots in banking, e-commerce, and healthcare.

NLP-powered bots that understand user intent and sentiment.

Predictive UX: Anticipating User Needs

Predictive UX leverages ML algorithms to anticipate user actions before they happen, streamlining interactions and reducing friction.

Real-World Applications:

Smart search suggestions (e.g., Google, Amazon, Spotify).

AI-powered auto-fill forms that reduce typing effort.

Anticipatory design like Google Maps estimating destinations.

AI-Powered UI Design Automation

AI is streamlining design workflows by automating repetitive tasks, allowing designers to focus on creativity and innovation.

Key AI-Powered Tools:

Adobe Sensei: Automates image editing, tagging, and design suggestions.

Figma AI Plugins & Sketch: Generate elements based on user input.

UX Writing Assistants that enhance microcopy with NLP.

Voice & Gesture-Based Interactions

With AI advancements, voice and gesture control are becoming standard features in UI/UX design, offering more intuitive, hands-free interactions.

Examples:

Voice commands via Google Assistant, Siri, Alexa.

Gesture-based UI on smart TVs, AR/VR devices.

Facial recognition & biometric authentication for secure logins.

AI in Accessibility & Inclusive Design

AI is making digital products more accessible to users with disabilities by enabling assistive technologies and improving UX for all.

How AI Enhances Accessibility:

Voice-to-text and text-to-speech via Google Accessibility.

Alt-text generation for visually impaired users.

Automated color contrast adjustments for better readability.

Sentiment Analysis for Improved UX

AI-powered sentiment analysis tools track user emotions through feedback, reviews, and interactions, helping designers refine UX strategies.

Uses of Sentiment Analysis:

Detecting frustration points in customer feedback.

Optimizing UI elements based on emotional responses.

Enhancing A/B testing insights with AI-driven analytics.

Future of AI in UI/UX: What’s Next?

As AI and ML continue to evolve, UI/UX design will become more intuitive, adaptive, and human-centric. Future trends include:

AI-generated UI designs with minimal manual input.

Real-time, emotion-based UX adaptations.

Brain-computer interface (BCI) integrations for immersive experiences.

Final Thoughts

AI and ML are not replacing designers—they are empowering them to deliver smarter, faster, and more engaging experiences. As we move into a future dominated by intelligent interfaces, UI/UX designers must embrace AI-powered design methodologies to create more personalized, accessible, and user-friendly digital products.

Explore more at Pixelizes.com for cutting-edge design insights, AI tools, and UX trends.

[technicallylovingcomputer]

How to create Dynamic and Adaptive AI for Mobile Games

In the competitive world of mobile gaming, creating an experience that keeps players coming back requires more than just stunning graphics and intuitive controls. Today's gamers demand intelligent, responsive opponents and allies that adapt to their play style and provide consistent challenges. Let's dive into how dynamic and adaptive AI can transform your mobile game development process and create more engaging experiences for your players.

Why AI Matters in Mobile Game Development

When we talk about mobile games, we're dealing with a unique set of constraints and opportunities. Players engage in shorter sessions, often in distracting environments, and expect experiences that can be both casual and deeply engaging. Traditional scripted behaviors simply don't cut it anymore.

Dynamic AI systems that learn and evolve provide several key benefits:

They create unpredictable experiences that increase replayability

They adjust difficulty in real-time to maintain the perfect challenge level

They create the illusion of intelligence without requiring massive computational resources

They help personalize the gaming experience for each player

Building Blocks of Adaptive Game AI

Behavior Trees and Decision Making

At the foundation of most game AI systems are behavior trees - hierarchical structures that organize decision-making processes. For mobile games, lightweight behavior trees can be incredibly effective. They allow NPCs (non-player characters) to evaluate situations and select appropriate responses based on current game states.

The beauty of behavior trees in mobile development is that they're relatively simple to implement and don't require excessive processing power. A well-designed behavior tree can give the impression of complex decision-making while actually running efficiently on limited mobile hardware.

Machine Learning for Pattern Recognition

While traditional AI techniques still dominate mobile game development, machine learning is making inroads where appropriate. Simple ML models can be trained to recognize player patterns and adapt accordingly:

"We implemented a basic ML model that tracks how aggressive players are during combat sequences," says indie developer Sarah Chen. "What surprised us was how little data we needed to create meaningful adaptations. Even with just a few gameplay sessions, our enemies began responding differently to cautious versus aggressive players."

For mobile games, the key is implementing lightweight ML solutions that don't drain battery or require constant server connections.

Dynamic Difficulty Adjustment

Perhaps the most immediately valuable application of adaptive AI is in difficulty balancing. Games that are too easy become boring; games that are too hard lead to frustration and abandonment.

By monitoring player success rates, completion times, and even physiological indicators like input force or timing patterns, games can subtly adjust challenge levels. For example:

If a player fails a level multiple times, enemy spawn rates might decrease slightly

If a player breezes through challenges, puzzle complexity might increase

If a player shows mastery of one game mechanic, the AI can introduce variations that require new strategies

The trick is making these adjustments invisible to the player. Nobody wants to feel like the game is "letting them win," but everyone appreciates a well-balanced challenge.

Implementation Strategies for Mobile Platforms

Distributed Computing Approaches

Mobile devices have limits, but that doesn't mean your AI needs to be simple. Consider a hybrid approach:

Handle immediate reactions and simple behaviors on-device

Offload more complex learning and adaptation to occasional server communications

Update AI behavior parameters during normal content updates

This approach keeps gameplay smooth while still allowing for sophisticated adaptation over time.

Optimizing for Battery and Performance

When designing AI systems for mobile games, efficiency isn't optional - it's essential. Some practical tips:

Limit AI updates to fixed intervals rather than every frame

Use approximation algorithms when exact calculations aren't necessary

Consider "fake" AI that gives the impression of intelligence through clever design rather than complex computations

Batch AI calculations during loading screens or other natural pauses

"Our most sophisticated enemy AI actually uses less processing power than our earliest attempts," notes mobile game developer Marcus Kim. "We realized that perceived intelligence matters more than actual computational complexity."

Case Studies: Adaptive AI Success Stories

Roguelike Mobile Games

Games like "Dead Cells Mobile" and "Slay the Spire" have shown how procedural generation paired with adaptive difficulty can create nearly infinite replayability. These games analyze player performance and subtly adjust enemy compositions, item drops, and challenge levels to maintain engagement.

Casual Puzzle Games

Even simple puzzle games benefit from adaptive AI. Games like "Two Dots" adapt difficulty curves based on player performance, ensuring that casual players aren't frustrated while still challenging veterans.

Ethical Considerations in Game AI

As we develop more sophisticated AI systems, ethical questions emerge:

How transparent should we be about adaptation mechanisms?

Is it fair to create different experiences for different players?

How do we ensure AI systems don't manipulate vulnerable players?

The mobile game community is still working through these questions, but most developers agree that the player experience should come first, with adaptations designed to maximize enjoyment rather than exploitation.

Looking Forward: The Future of Mobile Game AI

As mobile devices continue to become more powerful, the possibilities for on-device AI expand dramatically. We're already seeing games that incorporate:

Natural language processing for more realistic NPC interactions

Computer vision techniques for AR games that understand the player's environment

Transfer learning that allows AI behaviors to evolve across multiple play sessions

The most exciting developments may come from combining these approaches with traditional game design wisdom.

Getting Started with Adaptive AI

If you're new to implementing adaptive AI in your mobile games, start small:

Identify one aspect of your game that could benefit from adaptation (enemy difficulty, resource scarcity, puzzle complexity)

Implement simple tracking of relevant player metrics

Create modest adjustments based on those metrics

Test extensively with different player types

Iterate based on player feedback

Remember that the goal isn't to create the most technically impressive AI system, but to enhance player experience through thoughtful adaptation.

Conclusion

Dynamic and adaptive AI represents one of the most exciting frontiers in mobile game development. By creating opponents and systems that respond intelligently to player behavior, we can deliver more engaging, personalized experiences that keep players coming back. Whether you're developing a casual puzzle game or an ambitious mobile RPG, incorporating adaptive elements can elevate your game to new heights of player satisfaction.

The most successful mobile games of tomorrow won't just have the flashiest graphics or the most innovative mechanics – they'll be the ones that seem to understand their players, providing just the right challenge at just the right moment through intelligent, adaptive AI systems.

[learninghub-betasys-ai]

How AI is Reshaping the Way We Learn

echnology is rapidly transforming education. With AI-powered platforms, learners can now enjoy personalized experiences that adapt to their goals and pace. One such platform is LearningHub by Betasys, a free tool that helps students and professionals upskill with smart recommendations in AI, ML, AWS, and more. Explore it here 👉 https://learninghub.betasys.ai

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[teamarcstechnologies]

How Questionnaires and Technology Are Revolutionizing Fraud Prevention

Fraud has become a significant challenge across industries, from finance to healthcare. As criminals become more sophisticated, organizations must adopt advanced methods to detect and prevent fraudulent activities. One powerful combination proving effective is the integration of questionnaires and technology in fraud prevention strategies.

The Role of Questionnaires in Fraud Detection

Questionnaires serve as an essential tool in gathering crucial information from individuals, be it customers, employees, or vendors. Structured questionnaires can help organizations assess risks, verify identities, and detect inconsistencies in responses. By incorporating behavioral and psychological cues, they can reveal red flags indicating potential fraudulent intent.

Technology Enhancing Questionnaires for Accuracy

Modern technology amplifies the effectiveness of questionnaires in fraud prevention. Artificial intelligence (AI) and machine learning (ML) analyze response patterns, detect anomalies, and flag inconsistencies in real-time. Natural Language Processing (NLP) helps identify deceptive answers, while automated data cross-referencing ensures accuracy. Additionally, biometric verification and blockchain technology enhance security by confirming identities and preventing document forgery.

Real-World Applications

Many industries leverage digital questionnaires and AI-driven analytics to prevent fraud. Banks use them to assess loan applicants' credibility, insurance companies detect false claims, and e-commerce platforms verify users to prevent identity theft. Government agencies also employ AI-powered questionnaires in immigration and border security to detect fraudulent intent.

The Future of Fraud Prevention

With fraudsters constantly evolving their tactics, the future lies in adaptive questionnaires powered by AI, where questions change dynamically based on responses. Coupled with real-time data analytics and blockchain verification, this approach will further strengthen fraud detection and prevention.

In conclusion, the synergy between questionnaires and technology is a game-changer in fraud prevention. By leveraging advanced analytics and AI-driven insights, organizations can stay ahead of fraudsters, ensuring security and trust in their operations.

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[chiragqlanceblogs]

How Python Powers Scalable and Cost-Effective Cloud Solutions

Explore the role of Python in developing scalable and cost-effective cloud solutions. This guide covers Python's advantages in cloud computing, addresses potential challenges, and highlights real-world applications, providing insights into leveraging Python for efficient cloud development.

Introduction

In today's rapidly evolving digital landscape, businesses are increasingly leveraging cloud computing to enhance scalability, optimize costs, and drive innovation. Among the myriad of programming languages available, Python has emerged as a preferred choice for developing robust cloud solutions. Its simplicity, versatility, and extensive library support make it an ideal candidate for cloud-based applications.

In this comprehensive guide, we will delve into how Python empowers scalable and cost-effective cloud solutions, explore its advantages, address potential challenges, and highlight real-world applications.

Why Python is the Preferred Choice for Cloud Computing?

Python's popularity in cloud computing is driven by several factors, making it the preferred language for developing and managing cloud solutions. Here are some key reasons why Python stands out:

Simplicity and Readability: Python's clean and straightforward syntax allows developers to write and maintain code efficiently, reducing development time and costs.

Extensive Library Support: Python offers a rich set of libraries and frameworks like Django, Flask, and FastAPI for building cloud applications.

Seamless Integration with Cloud Services: Python is well-supported across major cloud platforms like AWS, Azure, and Google Cloud.

Automation and DevOps Friendly: Python supports infrastructure automation with tools like Ansible, Terraform, and Boto3.

Strong Community and Enterprise Adoption: Python has a massive global community that continuously improves and innovates cloud-related solutions.

How Python Enables Scalable Cloud Solutions?

Scalability is a critical factor in cloud computing, and Python provides multiple ways to achieve it:

1. Automation of Cloud Infrastructure

Python's compatibility with cloud service provider SDKs, such as AWS Boto3, Azure SDK for Python, and Google Cloud Client Library, enables developers to automate the provisioning and management of cloud resources efficiently.

2. Containerization and Orchestration

Python integrates seamlessly with Docker and Kubernetes, enabling businesses to deploy scalable containerized applications efficiently.

3. Cloud-Native Development

Frameworks like Flask, Django, and FastAPI support microservices architecture, allowing businesses to develop lightweight, scalable cloud applications.

4. Serverless Computing

Python's support for serverless platforms, including AWS Lambda, Azure Functions, and Google Cloud Functions, allows developers to build applications that automatically scale in response to demand, optimizing resource utilization and cost.

5. AI and Big Data Scalability

Python’s dominance in AI and data science makes it an ideal choice for cloud-based AI/ML services like AWS SageMaker, Google AI, and Azure Machine Learning.

Looking for expert Python developers to build scalable cloud solutions? Hire Python Developers now!

Advantages of Using Python for Cloud Computing

Cost Efficiency: Python’s compatibility with serverless computing and auto-scaling strategies minimizes cloud costs.

Faster Development: Python’s simplicity accelerates cloud application development, reducing time-to-market.

Cross-Platform Compatibility: Python runs seamlessly across different cloud platforms.

Security and Reliability: Python-based security tools help in encryption, authentication, and cloud monitoring.

Strong Community Support: Python developers worldwide contribute to continuous improvements, making it future-proof.

Challenges and Considerations

While Python offers many benefits, there are some challenges to consider:

Performance Limitations: Python is an interpreted language, which may not be as fast as compiled languages like Java or C++.

Memory Consumption: Python applications might require optimization to handle large-scale cloud workloads efficiently.

Learning Curve for Beginners: Though Python is simple, mastering cloud-specific frameworks requires time and expertise.

Python Libraries and Tools for Cloud Computing

Python’s ecosystem includes powerful libraries and tools tailored for cloud computing, such as:

Boto3: AWS SDK for Python, used for cloud automation.

Google Cloud Client Library: Helps interact with Google Cloud services.

Azure SDK for Python: Enables seamless integration with Microsoft Azure.

Apache Libcloud: Provides a unified interface for multiple cloud providers.

PyCaret: Simplifies machine learning deployment in cloud environments.

Real-World Applications of Python in Cloud Computing

1. Netflix - Scalable Streaming with Python

Netflix extensively uses Python for automation, data analysis, and managing cloud infrastructure, enabling seamless content delivery to millions of users.

2. Spotify - Cloud-Based Music Streaming

Spotify leverages Python for big data processing, recommendation algorithms, and cloud automation, ensuring high availability and scalability.

3. Reddit - Handling Massive Traffic

Reddit uses Python and AWS cloud solutions to manage heavy traffic while optimizing server costs efficiently.

Future of Python in Cloud Computing

The future of Python in cloud computing looks promising with emerging trends such as:

AI-Driven Cloud Automation: Python-powered AI and machine learning will drive intelligent cloud automation.

Edge Computing: Python will play a crucial role in processing data at the edge for IoT and real-time applications.

Hybrid and Multi-Cloud Strategies: Python’s flexibility will enable seamless integration across multiple cloud platforms.

Increased Adoption of Serverless Computing: More enterprises will adopt Python for cost-effective serverless applications.

Conclusion

Python's simplicity, versatility, and robust ecosystem make it a powerful tool for developing scalable and cost-effective cloud solutions. By leveraging Python's capabilities, businesses can enhance their cloud applications' performance, flexibility, and efficiency.

Ready to harness the power of Python for your cloud solutions? Explore our Python Development Services to discover how we can assist you in building scalable and efficient cloud applications.

FAQs

1. Why is Python used in cloud computing?

Python is widely used in cloud computing due to its simplicity, extensive libraries, and seamless integration with cloud platforms like AWS, Google Cloud, and Azure.

2. Is Python good for serverless computing?

Yes! Python works efficiently in serverless environments like AWS Lambda, Azure Functions, and Google Cloud Functions, making it an ideal choice for cost-effective, auto-scaling applications.

3. Which companies use Python for cloud solutions?

Major companies like Netflix, Spotify, Dropbox, and Reddit use Python for cloud automation, AI, and scalable infrastructure management.

4. How does Python help with cloud security?

Python offers robust security libraries like PyCryptodome and OpenSSL, enabling encryption, authentication, and cloud monitoring for secure cloud applications.

5. Can Python handle big data in the cloud?

Yes! Python supports big data processing with tools like Apache Spark, Pandas, and NumPy, making it suitable for data-driven cloud applications.