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mariacallous · 6 months ago

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On Wednesday morning, a small group of people huddled over their phones at the foot of the giant glass skyscraper that houses Uber’s London headquarters. They were running an experiment in an attempt to solve one of the greatest mysteries in the platform economy right now: how Uber’s algorithm calculates driver pay.

Beneath flags and banners calling on Uber to “Stop Dynamic Pricing,” one driver ordered a ride, acting as a customer to Heathrow Airport, and received a quote for £46. Seconds later, the job pinged up on the phone of a fellow protester, who had told the app he was ready to drive. His fee? £26.

For years, Uber has taken a commission of 25 percent from London-based drivers. But the company told drivers in January 2023 the app was updating its pricing model, a change it said was necessary to make fares appeal to drivers and offer the lowest pickup time for passengers. Yet the people behind the wheel say those changes have lowered their wages and made how they’re calculated impossible to understand—sparking fears that dynamic pricing is offering drivers across Europe and the US personalized wages, a charge that Uber denies.

“A few years back, the fare was transparent, you used to see how much the passenger was charged,” says Farah Musa, an Uber driver since 2015, who is taking part in the protest and 24-hour strike. Now the information is hidden, and he doesn’t understand how the fare is calculated. “Dynamic pricing is not good for drivers. We are being cheated.”

Uber’s “surge pricing” feature used to kick in only during busy periods, making rides more expensive to incentivize drivers to log in to the app. Now, however, the app uses variable or “dynamic” pricing all the time, says James Farrar, the former Uber driver who won a landmark case against the company in the UK Supreme Court and is now director of nonprofit Worker Info Exchange. “We’ve gone from a completely transparent pay and pricing system to one that’s now completely opaque,” he says. “People literally do not understand how the pay has been set, how the work has been allocated, and how they may have been profiled in that decisionmaking.”

It’s only Uber that knows how the wages are calculated, says Lucky Matthew, at the London protest, who says he now receives £400 ($509) per week less than before the pandemic. “We’re working the same hours as before, the cost of living is going up, but wages are going down.”

Many of the drivers at the protest have been asking their passengers how much they are paying for the ride, and their answers have unleashed a wave of anger toward the company because they claim Uber is taking much more than a 25 percent cut. “It’s a scam,” says Cristina Ioanitescu, who drives an Uber XL and carried a sign reading “Smart Pricing = Smart Cheating.” “It’s a lot of stress for us.” Uber says that although commission fees vary, they can sometimes be as low as 0 percent and drivers can see the fare before accepting a trip.

To understand how the fares are calculated, Uber drivers have not only been scrutinizing the passenger fees—they have also been poring over the company’s financial results. In the company’s February earnings call, a comment by Uber CEO Dara Khosrowshahi prompted concern among union representatives in the US and Europe that the company was personalizing the wages they were offered based on the data collected about drivers in the app.

“What we can do better is actually targeting different trips to different drivers based on their preferences or based on behavioral patterns that they’re showing us,” Khosrowshahi told investors in that call. “That really is the focus going forward.” When WIRED asked Uber about Khosrowshahi’s comments, the company denied it was personalizing prices for drivers based on who will accept the lowest fare.

“Uber reviews real-time information such as traffic and the distance to the rider to provide the best price to appeal to the drivers in the area,” says Caspar Nixon, Uber’s spokesperson. “All pricing is based on aggregate data, not personalized rider or driver data.” Drivers also receive a weekly statement telling them how much their passengers have paid versus the commission Uber has kept from their fares, Nixon adds.

Yet to Zamir Dreni, London vice chair for the App Drivers and Couriers Union, Khosrowshahi’s comments were proof enough. “They are profiling drivers,” he says. It’s not only London where drivers are suspicious of personalized pricing. “This has been a mystery for years now,” says Amrit Sewgobind, the representative for gig workers at the Dutch trade union FNV. Uber driver chat groups are now filled with screenshots as people try to compare journeys of similar distances that resulted in different fares, he says. Last summer, Sewgobind tried to better understand these differences by arranging an experiment in Amsterdam West, where he compared the various fares being offered to a small group of Uber drivers, although he says the results were inconclusive.

Drivers in the Finnish city of Jyväskylä also protested last year against Finnish food delivery platform Wolt, which in 2023 shifted from a base payment to a new pricing model that is calculated according to a variety of factors ranging from consumer and merchant location to weather and the weight of an order. Wolt told WIRED that no courier behavior data is used in that calculation.

“They don’t have a workforce to optimize. They don’t have an asset base to optimize. The only thing they have to optimize is the algorithm,” says Farrar of companies operating in the platform economy. “Dynamic pricing has been introduced as a means to charge customers more on average and to pay drivers less.”

Back at the protest in London, the Uber drivers are determined to be heard by the company in the skyscraper above them. Mohammed Farooq says the erosion he has witnessed in his pay over the past four years was enough to bring him here, to his first protest. “Unless we protest, Uber is not going to give us any rights,” he says.

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nagalias-mindscape · 10 months ago

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When i started this thowing rock challenge for My Time at Sandrock, I went into it expecting to- you know- having to do a lot of quarrying and mining (mostly the mining). Relics are decent stat bonuses, and they provide passive relationship points to everyone who visits throughout the day. Small, yeah, but they take up so little room.

You can also donate one to the museum to get the rewards from that, and reputation points for your workshop rating. Already got the musical shotgun before the bridge was ever built. You know- that thing you get for donating 100 different items? Yeah. I have that- not that it's doing me any good, what with shotguns being a banned item this run. (Also, the phone-keyboard weapon 'Ragequit' is just... *chefs kiss* brilliant.)

What i did not expect, but really should have, was the sheer amount of data discs I'd collect and their game breaking value. 3 Gols doesn't seem like a lot, but you earn a bunch when you clear out each ruin layer of its sand and stone. And the price is pretty often closer to 4 - 5 Gols instead of 3, due to inflation. And you can sell them in a pretty decent number of places.

Blue Moon, Commerce Guild, By the Stairs, Mask Man, City Hall, Water World...

You basically hold on to Data Discs for one of three reasons alone: either you need to research something at Qi's, or you have a nasty spending habit and need to store Gols in a form that isn't easily spendable. Or you need to buy crops. I have... set myself back a bit by forgetting to buy what I need before selling them to upgrade my house and buildings.

And sure, 2k to 5k for a full stack of data discs isn't much depending on the inflation rate, but I can get near about half a stack from just a full day of mining.

Splitting my time between an A-B-C pattern of:

A: Commissions + sand fishing (dried sandacuda is OP for early game, and it's carrying me pretty well going into Gecko Station. I only need ~13 to regain full SP, and I can make waay more than that in my drying racks.

B: Commissions + Full Day Ruin Diving

C: Commissions + Side Quests + Timed Quests + Water/Fertilizer Top-up on Garden + Buying stuff in town I need (mostly water, more fertilizer, straw, and food)

I'm pretty much loaded. All throughout A-B-C, I've got items in my smelters and processing machines to make commissions easier. I've also got my garden pumping out Sandrice like there's no tomorrow- because there will be no tomorrow if I run out of sandrice and can't fish for more sandacuda.

But those data discs are basically free money, since they only get used to research crap and buy crops from burgess and zeke- which I then in turn make into even more money.

My haul from just layers 1 & 2 of Eufaula Salvage Ruins and an entire day. I get waay more when I go into the lower layers of the ruins.

Sure, I smelt down the ore into ingots and sell those, craft them into parts and sell those, and even turn in the crafted parts for commissions, but I also sell those data discs because- what else am I using them for? Not relics- catori screwed herself out of that by giving me a relic restoration machine I still haven't 'donated' back to her.

#text #mtas

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my-jokes-are-my-armour · 11 months ago

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...

I don't really know why I suddenly returned to my old series during my vacations, but revisiting some Star Trek series I consumed in my teenager years to late teenager years made me realise something : I always loved the character that was the most unearthly for each series. Spok, Data, Odo, Seven of Nine.

And then I stumbled on that on a reddit thread...

I feel so seen 😅.

I won't go to much for Spok and Data (for the moment at least), but they were almost my first blorblos ever ☺️. I may come to Seven though.

I wanna talk about Odo today and especially in a ace point of view.

Important : this is just a character analysis through my own experience and how i connected not any formal lecture on the subject !

Note : I will switch sometimes between "he" and "it" for Odo. As his specie is basically a fluid with technically no gender at all. He primarily imitated a male person and stayed that way. Has Odo self gendered male in the end ? Maybe. Let say he is gendered that way in the show. That's why I use "he".

A little bit of my trekky journey

The funny part is that I was a real trekky for many many years. My father wanted me to discover the show he liked when he was younger and I became the 2.0 version of him, being obsessed with it ☺️. My parents kindly participated with my passion. They bought me the first parts of the officials Star Trek files. But then they choose to teach me the value of the product they were offering me with work.

I didn't have pocket money except from my grand parents sometimes. So they told me : you do things in the house, we give you a bit of money for it and you can buy your own stuff with it. It was 10Fr for each helpful stuff.

Needless to say, I became very good at washing dishes, cooking and doing the laundry very early 🤣. I needed 70Fr, which is about 10-11€, every two weeks to buy my files and VHS. It became a bit harder when we switched to euros, because 10Fr became 1€ earn for the house chore, and the price of the files grew rapidly... So I never finished that collection. But as you can see I have a solid one lol. They kept the VHS collection as I had no place to store it when I first moved out.

I remember liking a lot this period because I could buy my stuff and then we had a cool moment of bonding together with my parents watching the VHS in the weekend.

The sad part is that is that I never could complete my collection. Too expensive to a point. Saddly, I don't have much about Odo in my files, except for its Starfleet one and worse for Seven of Nine, with nothing at all. But I guess the character was not added yet to the show. I had very few VHS of Voyager at the time.

First impression on Odo and comparison to Data

As many I guess, I wasn't really thrilled at DS9 in the first place, but rewatching it, I found it extremely good now. I had the same feeling with Voyager which I was really appealed to, once Seven was added to the crew.

Those four characters I relate to the most have in common a rejection or a lack of comprehension of human emotions or behaviours. But Odo was different in a way that I can recognise a lot of myself nowadays in terms of development around my own journey discovering my sexuality.

I remember that when I first saw its design I was like. Oh they are trying to make a new Data character.

But no, it is very different. Odo has emotions, strong emotions, and understands them but he cannot fit, because basically it is not humanoid, he is a sentient puddle of goo... It learned to take a humanoid male shape to interact with the most common form of sentient beings around and the equipment of the ships.

If his shape technically makes it difficult to express clear emotions as he is sleek as butter, he can, and does it a lot. So he is not an emotionless or emotional repressed character (although in some aspect yes... 🤔). And through the series, Odo grew on me for its grumpy personality hiding a very sensible and traumatised being.

There is a common ground between Odo and Data in the fact that they are "unique" creature of there kind evolving around people and trying the best they can to be a part of the community. They have a similar arc or steps of development : strange to others, link with some people, explore emotions, try to mimick what they don't understand, link with more, acceptation, deep frienships to even love experiences, sacrifice. But they have opposite feedbacks and starting points.

Data don't feel per se and even with the integration of the emotion ship he has a lot to learn. But he is ready for all experiences, to learn to feel, and explore humanity.

Odo doesn't need to learn emotions, he already feels. But he begins his life among humanoids with abuses. Everything that he has learned to become more "human" comes from pain. So even if he tries to fit, he is extremely shielded and tries to prevent other to see how vulnerable he feels in reality, to escape the inevitable pain if he is not what people expect. Also, Odo can connect with people only if he makes the constent effort to be something he is not.

They are both children learning, but one of them is beginning his journey with strong traumas. So each of their step towards fulfilment is hard but not for the same reasons.

Also Odo has a big journey about love and discovering what he needs and how different his experience is. He doesn't understand sexual attraction and mating. And the traumas make it even harder for him to figure out how it works for him. He needs a lot of guidance that he cannot always accept or precise rules to know how to function as expected in certain situations. He tends to toss aside violently (verbally) those who cannot give him that when he feels cornered.

I think there can be a lot of readings for this character for many people but, in my case, looking back at him now, I find that this strange position Odo had in a community, I subconsciously felt it on the sexuality part of myself. I couldn't connect with anyone, even my friends on the subject... I was the alien. I tried a lot, I mimicked but it failed and it made me sad, until I understood how it worked for me.

Which leads me to my next point.

Love stories and unearthlyness

Of all my blorbos in Star Trek, I feel like Odo is the most unearthly and in the same time the most relatable for me.

For my three other blorblos, I never been really interested in their love stories or sexuality - I was attracted for other things in them - but I appreciated that "love" was not much part of their main journey or that they discussed more about the general feeling than making out with other characters. But for Odo... dear lord! I dived head first in his loved stories because it was speaking to me. He has several love stories and some are central to his character. But in many aspects of this part I was finding myself in his struggles.

He had feelings for others, he could clearly fall in love sometimes, but couldn't experience it like everyone. He had some pationate kisses and some intimate moments here and there, but the love moments I connect the most were when he shared what he is with some characters, in a non flesh way, if I can say so.

If I could make some conclusions directly, I would say that Odo begins as a hetero asexual, sex repulsed, to demisexual after he discovers how to connect with people and he creates a deep emotional link with some of them. He even discovers that, even with members of his own race which have the perfect form to union for him, he doesn't feel anything because the emotional link is not there. And to discover that, he goes from mimicking and mimicking again and again, failing over and over until he muddles his way out of it, finding fulfilment and finally can love the way he needs.

The fact that he isn't humanoid, even solid, is central to him. He states so many times and tries to formulate in many ways that what we can see is not what he is.

For a long time he rejects parts of humanoid's interactions that involve feelings. He freezes most of the time when being hugged. And avoid people with those kind of behaviours.

Me in my corner 🥲👋. Not to this extend but the inconfort is real.

In a way those scenes have a comic aspect but for those who can relate to him, even little, this isn't as funny.

For him, a big part of these reactions comes from the fact that in his experience, what he doesn't understand and doesn't know how to react to, means pain. This is how he was taught in the first place. Also, he is so different in nature that his needs on the subject are totally unreachable. So he has to learn to find the middle ground to live his experience in a group of people that technically cannot match.

For the most part, he is pushed by his friends to open up to the experience of bounding first and then making out, which became the hardest part.

Through his interactions, he becomes more and more aware of how to express love and he shares with some people that way, but he discovers also he is so different than his love isn't understood. Misunderstood for what his feelings are, in nature for him to the others, and misunderstood for what he can feel sharing the physical love with his partners.

I was so heartbroken by some of those moments as the link is created but the difference is too big to make the link hold. And I was so rewarded in others when he is accepted as he is.

The main emotional links

- Quark frienship.

Odo develops some friendships and interesting connections along the way, but the strongest for me is with Quark.

Basically this is the bromance involving one grumpy and closed character, and another that is very loud and annoying to the grumpy one. They are opposite. Odo is order. Quark is chaos.

They have a love/hate relationship with a lot of humour resulting of their interactions but they read each other is many occasions and sometimes it becomes emotional.

I won't get over that face Quark make when Odo (fusionned with someone else's personality) freely expresses his affection for him ☺️. I could ship them all day.

- Garak friendship

Garak is a very strong character with many layers. Odo and him link for good through a very tough experience, as Garak needs to torture him at some point.

In a lot of aspect that illustrates what Odo went through to become a valid humanoid form. But this time we can connect as he is not a suffering in silence puddle but a visible hurting humanoid.

But Garak and Odo link because they mirror themselves, through pride, loyalty and betrayal. Through the pain they feel, hidden inside, and their sense of belonging, or should I say not belonging...

The pain Odo is enduring turns back on Garak and makes a difference for his future moral choices. Also Garak will keep Odo secret he learnt from the torture. The secret that makes then alike. They are homesick because they are desperately lonely. They are the enemy of the community they try to fit in because their species are.

From that comes a strange friendship rooted in suspicion but understanding.

And by the end, even Garak wanna help Odo finding his way through his love experiences.

- His love story with Lwaxana

This one is rewarding and heartbreaking to me. Lwaxana is a Betazoid with a huge libido. She crushes on Odo who tries to avoid her at all coast as she tends to cornering him into a physical interactions and a need for mating that doesn't suit him at all.

But she is the first to show him he can be loved as he is. We discover with her that he is ashamed to be different. That he doesn't want people to see him in his natural form (liquid) even when overdoing staying in a solid form is painful to him.

But stuck in an elevator with Lwaxana he refuses to return to his natural state in front of her, even if he reach his limit. She teaches him that she also is more than what people sees, and offers him a safe place to be what he is.

Much later, they develop some bounds as she is trying to escape her husband who wanna take the baby she carries as soon as she gives birth. At first he is guarded, but Lwaxana finds her way to share some soft moments with him, in a way he didn't know he was capable of. She needs confort, he doesn't know how to give her. Cornered, he find a way.

That moment unlock some other moments where she participates in his own way of bounding as a shape-shifter. They are on common ground, with no sexual things in the middle and they are happy together.

He offers to marry her to counteract in a legal way the fact that her current husband has a property right on the child she carries. And during the ceremony, this is the first time he expresses his love for her.

First he tries mimicking what is excepted of him, telling that she is intelleigent and beautiful. But the husband, present to the ceremony to stop it, sees through it and Odo finally tells the way he feels. Even his friends that know him for years are embarrassed to discover on this occasion how lonely he was feeling all this time and that they don't know him that much, whereas this woman who he met so little changed his life for the better.

This love is sincere but as an empathe she understands than Odo does not love her the way she needs. Odo would be fine with her company, sharing moments like they did before. But she needs more than he can offer her.

He loves her. But she is in love with him. And he learns that is different and not sufficient. Also she spotted his true repressed feelings for Kira, who I would speak about after. So she breaks with him.

She did it in the most gentle way she could, but I had this experience, without knowing that I was actually asexual and it hurts a lot. I tried. I made some tough choices for me, just to be rejected without explanation (or one that I couldn't understand fully on the moment). The real explanation was that I couldn't give the man what he needed. But he never realised how much efforts I put in this relationship and it broke me in the end. So this is what I see there.

- The love of his life, Kira

Kira is a very strong character that can be harsh to others, because of her own harmful past. She is passionate and all fire sometimes. She is very loving and tender on the other side.

The development of this story is more classical, with two people loving each other but don't express their feelings, waiting for the other to make the first step to no end.

There are misunderstandings and errors made on both side, they struggle, living their life away from each other, having other experiences, but then true love wins (almost).

This is the kind of love he is ready to betray for. This is the kind of love she is ready to let go for his happiness.

Kira is the one Odo wants to connect the proper way for this to work and all his struggles in other love relationships prepares him for that and in the same way prevent that from happening for a long time.

They learn each other progressively but the guarded nature of Odo is an obstacle. In the end, she is the one he finally opens up to everything that he is, even if the experience may not suit a humanoid form. It happens when Kira realises that Odo doesn't think she can love him the way he really is.

I love deeply that moment when he takes a pure energy form and envelopes her and she responds with wonderment and joy.

Kira proves her love for him several times, especially in the way she knows him and respects how he is. She is the one to understand the best his pride and need to keep some things hidden. She puts words on it when he can't so other wouldn't hurt him trying to make him react in a way they consider better.

They are two hurt people who learn the shape of the other through love.

Unfortunately like most of pure love stories, it is doomed. He has to return to his people to save the entire species so... they won't live together happy ever after. But we learn at some point that his love for her never faltered, even centuries later.

I love those kind of story with pure feelings and emotions ☺️.

From nothing to something

They had unearthly creature before in Star Trek, but when they were not machines, they were almost exclusively humanoid for evident reason of human playing them 😅. I liked the different society point of views making points for our own. But to me, Odo is the first really unearthly main character. Because he is technically not relatable in his true form.

How should I connect emotionally with a puddle ?

And for a very long time, in the show this is the underlying issue Odo has with everyone but for the reversed reason. He is puddle, how could he connect with solids ?

The thing is that Odo is seen through the filter of those who are the norm. And we meet him when he has a stable apparent relationship with others. We learn the underlying struggles and pains he experiences, discovering the differences. And those differences are relatable because we can question ours.

The thing is that we don't see for a long time that he hurts to be different as he appears rejecting or snobing humanoids. Attack is the best defense...

And as I said before, this comes from how he learned to adapt.

His very existence is "nothing" and he has to grow from that in a very traumatising way.

He learns very late that his own people abandoned him to be found by humanoids as an experiment to connect with us. But if he was aware of himself, he wasn't aware of anything else. Changelings are not meant to be alone. They live in total fusion in a sort of sea of them.

So from the start, he is fucked up. And those who found him didn't understand it was a sentient creature for a long time. They experiment on him as it was a inert matter. He exists but has no properties that we can attribute to a living organism.

He was found and labeled as "unknown sample / nothing" in cardassian (Odo'itil - in short Odo). He was one of its kind in a world of entities that couldn't understand him and that he couldn't understand either. So basically he experienced torture until he found a way to communicate, through changing form and mimick. But yet again the experiments continued until it was proven to be sentient.

Odo has a lot of resentment from that period.

Ironically, he was not a good shape-shifter, that why his face looks the way it is. And his face is a pale copie of the face of the man who experimented on him, this harmful "father". Also he kept the name Odo as designation. Nothing.

His relation with his "father" is very conflicted. The first time they met after Odo went away from his lab, it triggers a very powerful unconscious emotional response. And his father recognise the extend of the harm he did to him, and he never was aware causing it. He finally found a way to bound with this man, recognising that his father loves him and is hurt from the cold separation. Odo doesn't forgive totally but he opens a door to a future collaboration.

I like the evolution of his psychology around it and through his name also. He explains that at first when people called him Odo, he was hearing "nothing". So for him, people considered him to be nothing. And when he made some real friends, he finally came over that pejorarive meaning around his existence, he began to hear a name.

He achieved to become something out of nothing.

The desire to link and the demisexuality

Odo doesn't know much about himself except that he is. Though he has a need to link with other that comes from his own nature. He doesn't know where it leads.

His first links are made in the most humanoid way possible. He doesn't want to be weird. He is mimicking some things to share moments with others, like drinking or eating. He doesn't need to and cannot really absorb things. But he does it anyway and find some fulfilment to simply be with them, talk and share.

The Changellings (his species) don't like solids forms of life and abhor connecting with them. They are almost repulsed by the idea of binding physically with a solid, because their link (fusion) is much more. But the links Odo makes aren't physical ones.

While he doesn't know the existence of his own species, Odo has the same internal repulsion over everything that imply physical link, so especially everything around sexuality, because to him the way it is done by humanoids is uncanny. It lacks something but he doesn't know what exactly. But he knows that what is the most strange to him is realated to the love feeling. For him what he observes from people in love isn't what he experiences and all physical attraction is weird and disgusting.

He often verbally states in a very crude way that he doesn't understand the need humanoids have to mate and they biological needs for pleasure. Also their rituals to link for love is the most abstract thing to him. He acknowledges the feeling, not what can accompany it.

But he does develop feelings for others and some attraction. He is even attracted to female humanoids in general. He doesn't want to make out but he can experience a kind of pull and curiosity. But as soon as he has to interact and he recognises attraction from the other part, he bails. He has to be forced into something to begin to understand bits of it.

He continues to live the experiences about linking with others the same way he was taught to interact with people in the first place. Meaning, escape from pain to find where it doesn't hurt. And it is painful to see him to go through that for love too. He naturally tries to avoid pain where he thinks it is and ends up in being forced into a situation extremely inconfortable for him, struggling to find the best way to find a new balance in his emotions and in sensations in which he finds no pleasure.

When he meets Lwaxana, she is the most disruptive and invasive person ever. He doesn't have any feelings for her and she is forcing her way through him to get that response out of him. But she is the first to see what is the problem and offer a solution that his not harmful to him. She is the first whose love reaches him. And he began to love her in his own ways. This is not enough of course...

When he meets his people, he experiences the first fusion of his life and the experience is the definition of what he needs. But... soon he realises that even if this is the equivalent of his biological needs, he doesn't feel for it at all. Later, after some other steps in his journey to discover love, he tries to share with a Changelling what he has learned and the experience is unconclusive for both of them. The Changelling doesn't feel anything for the act as a solid. Neither does Odo, even if he is sure he made it right. The Changelling tries to force the idea that their natural way of linking is the best for him and he has to abandon his humanoid habits. But still he doesn't feel that way. Like yes, this is the most rewarding thing except there are no feelings.

At some point, because he choses humanoids over his own kind, killing a Changelling that was harmful to his friends, he is punished by his people and rejected. They made him human, keeping his imperfect face as a reminder to how bad he was even as what he was supposed to be. So he has to live like what they consider a poor and disgusting life. Odo has to learn a lot of things back but in the same time, he experiences for the first time some simple pleasures he couldn't grasp before. When he can finally revert to his natural form, he uses this experience to connect better with others has he understands now a bit more about their needs.

Odo is the one that has to make the extra steps in every direction. Steps toward humanoids who can learn to accept him and care for him but without fully understanding what he is and ignoring a lot of time is personal needs. Steps toward Changellings who can understands what he is and can offer him to fulfil a lot of his needs but won't understand some of them that are vital to him, like the need to be loved and to love, something that he developed staying with humanoids and that they consider a defect.

To both side, on the aspect of love he is incomplete.

The Changellings are purely asexual and sex repulsed, if I had to make a comparison. They are experiencing things completely detached from love in all its forms. In their norms, he has to remove the idea that this feeling is necessary to his existence. They try to cure him from that, educating him to the way his species do things. But to him their way to link is incomplete for his personal development.

On the other hands, to him, the humanoids are sexual beings with a lot of needs he can't grab. To their norms he is just not trying hard enough to get what he wants. They see his need for love, they recognise that he can feel, but the answer is often the same and not very helpful in the form that that is take. Try again. They don't acknowledge that pain and fear on this subject are two overwhelming obstacles for him and that they pushes are, more often than not, harmful. But with them, he develops those feelings, painful steps after another, finding the shape they have.

He cannot find fulfilment in both of the worlds he knows, until Kira.

Well, to be fair, he has an experience with someone else, with whom he falls in love. He has sex with her and discovers he can find pleasure in it. In the demisexual way. And that's the key for him.

But that person has to leave him behind. And as I explained before, his own experience of life made that kind of thing very harmful to him. That is a step that pushes him backwards for quite some times.

The thing I relate the most in this experience is when he asks the woman if he did good as it was his first sexual experience ever. She replies that she couldn't tell it was. And he is happy to have satisfy her needs and feel pleasure too. But for me, the way it is said is a lot like, I hope I did everything right as a solid demands it, so I won't be punished. Well I had this experiences too. Trying to match expectation and being punished for not doing good enough...

And what kills me is that Odo does good. He makes real progress and is about to maybe have a positive experience from it. And in the end he is punished by the events themselves, not that he didn't anything wrong on the thing, but he did wrong to have even tried...

So his first real step forward in his journey is rewarded with pain shortly after. Something he will struggle to overcome to try new experiences and many are pushing him. So you can guess the reaction...

But from this experience he has to learn that, for him, love is possible only if a strong emotional connection is made. He will need some more time to assimilate this.

And of course, in the end, Kira is the one that checks all the points.

After that he will try to overcome his problems to express his feelings and fear to lose the only one with whom failing would be too painful. And, once again, because he always experience the things the same way, it is cornered that he makes the final step.

In the end, he has to leave her but their separation, even if bittersweet, is tender, full of understanding and love.

Final word

I hope that I wasn't too boring with this long analysis for a character that is not in the fandom of this blog.

Odo is a complexe character, and quite gray. Yeah he did bad things too. I made this analysis through the specter of my reading of his sexuality mostly and my own experience pov. But this is a character interesting in many other aspects. He keeps a lot inside and when things come out we aren't really prepared.

I don't want to go specially far in the fandom online. I don't know what is the state of it really, and I stopped in the middle of Entreprise show as I didn't connect with the characters. I don't know either if you would like to learn more on my blorblos from the past. Those from Star Trek but I have some others. I inaugurate the tag "blorblo from the attic" for the occasion lol.

Have a nice day, and I leave you on a Odo Quark smiling to each other moment ☺️.

Additional image ressources [x] [x] and [x]

#character analysis #odo #tw: abuse #tw: torture #for those who are sensible over the subject #long post #removing tag for less visibility #blorblos from the attic

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sillyfudgemonkeys · 1 year ago

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I mean, given that P5D flopped and Atlus stopped making dancing games but kept/keeps on making P5 spinoffs I'm doubtful that Atlus would make tactics games whether P5T does good or bad (plus I feel like its every other time I hear about it I hear a persona fan mentioning they're not a fan of tactics games so it's def not just a thing on this blog)

Hahahaaaaaa......yeah............

Tbf I don't see a REASON for a dancing game atm. That's more of a game to celebrate the music (or throw it in the trash and set it on fire like P5D did, RIP to P5D you shouldn't have come out when you did)

Also tbf PQ2 didn't sell THAT much better (I think the sales were fairly within what Atlus is/was used to tho? only like 20000 less....then again that might've been OLD data I was looking at). And there hasn't been a Q game since....but tbf Atlus isn't popping them out AS FAST as when they were having their P4 era. (we almost got like 3 games in one year? TT0TT god everything was moving so fast in that era)

Probably cause of quality contr-I can't even finish that sentence.

Ahem. Probably cause of scope maybe.........except PQ2 was roughly the same story length as PQ1......or at least ONE SIDE of a PQ1 playthrough (tho some bits of PQ1 did repeat on each side, A LOT didn't). (there's also the fact they released it on a dying/dead console ahhhhhh, unrelated to scope but still TT0TT)

Uhhhh ummmmm, oh! P3/5D! Right- no I notoriously lambast them for CUTTING content that a single P4D could handle. Half the "story" and less songs. (of course this is considering P3D, P5D, and P4D all separate games on their own....which they are....and were sold as...................separate games......full price....games.....)

Ok ok Strikers! Yes Strikers. That had the scope that matched/exceeded Arena/Ultimax.... at least story wise. But....no one talks about Strikers for some reason. I thought y'all where hyped??????? It seemed to have sold well, but I dunno if that means it's liked..... (I have a VERY small sample size, but outside myself, all the people I've talked to IRL said they hated P5S TT0TT)

Wait why am I bringing this up? Maybe it's cause I miss the P4 era. TT0TT ajfksjf;d

Oh! No no, it's that, P5S is like the most successful P5 spinoff imo (didn't look at the sales but I think it might be the best selling Persona spinoff in general)....but we also haven't had a P5S2, or DLC for it (surprisingly/unfortunately), or another Persona game just like it (like P1S or Raidou S or yadda yadda).

That being said.......P5S was made with another company so....yeah...... that could be why jfsdljafdsakj

Unlike P5S, Dancing and Qs are made in house, P5T is too? I haven't been paying attention. TT0TT It could be they are just focused on T and...."Asa"? and P3R and/or something else. So that could explain the lack of another dancing game (or Q). Plus, again, the dancing games are more of a celebration. I can see a P5D2 happening as we get closer to P6 tbh (if not a P3/4/5D PS5+others port). (and I'm sure they are figuring out how to port Q to other places now they don't have the dual screen). I dunno, this part went on longer than I thought @_@ Just woke up and I'm rambly sorry

I mean Atlus has had the chance to do another Tactics game for years with the DeSu franchise, and those aren't even connected/have to be connected in a single timeline! And people are still waiting on 3! TT0TT So yeah I can see them just dropping it orz

(Yeah I've asked others IRL and they weren't exactly excited either TT0TT Tbh as long as I get another version of this artstyle again I'm fine with that, doesn't need to be a Tactics game.)

#'silly dont you hate most of P5's music' I do. Most of it tbh but Ive always stuck by the fact P5D was released TOO EARLY #Sure base P5 had the most songs on its OST but it had no spinoffs at the time (P5D WAS THE FIRST SPINOFF TT0TT) the anime was still airing!#it was doomed from the get-go and that's a shame for the fans orz #p3/5d should've been released after P3R tbh at least with how all this stuff is panning out #silly answers #silly asks #P4 manga is better than the anime anyway #'you didnt smear p5x' i'm biased......jfksajf jk it's also not technically fully out yet last time i checked either #i dunno why I went on for so long lkjfdskjfa gotta wake up! TT0TT

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opinions-about-tiaras · 9 months ago

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I work at the coal face here, so I feel like I have some things to add.

By "at the coal face" I mean "I am employed in a technology role at a company that is essentially the platonic ideal of the business use-case for LLMs." (I try and avoid calling them "AI" because they're not, but I suspect I've lost this philological battle.)

I work at a major (Fortune 1000) real-estate services, property tax services, and credit analytics company. Literally 100% of our work is gathering and analyzing data and providing conclusions, business plans, recommendations, professional and legally actionable tax advice, and other related services based on that analysis... but we are not, ourselves, a tech company, despite an intense branding push on the part of our corporate masters. We have specialized in-house algorithms that have proven to be effective at things like "analyzing and pricing flood risk better than those of competing companies" but that's about it.

You'll not the highlighted part of my last paragraph. I'll come back to that.

Like everyone else in the world, our leadership is going pretty hard in on LLMs. Because we're an ideal use-case for it, right? We do nothing but mess with data.

We struck a major deal with Microsoft for a huge implementation of Copilot, there are trainings and seminars like I've never seen to teach people what it is and how to leverage it, etc. We're spending a lot of money on this.

The results so far?

I'm going to give Copilot credit; it's fantastic at automating away a lot of basic clerical work. It can write lengthy emails that are meant to be nothing more than straightforward conveyances of information like nobodies business if you feed it the information. It can take notes on meetings in a quick and effective manner, its algorithms having a decent understanding of what bullet points to distill out of a ten-minute conversation. We've even been having it work the camera at major company presentations and its better at it than most people are, certainly better than prior "tries to focus on the speaker and their presentation automatically" pieces of software are. A bunch of other things that have to be done but are basically busywork.

This is all very useful. But that's about where its usefulness ends.

The actual BUSINESS business side of things is struggling mightily to find uses for the thing despite massive corporate pressure to do so. And the issues there are twofold.

The first is that the analytical tools we use primarily spit out data... but the core of our business is interpreting that data accurately, and continuing to insure that the data, itself, is accurate. I mentioned flood risk previously? Part of what we do is that every couple of years or so, the guys over in Business Intelligence need to actually start going through the real-world records for what floods happened and where, running them against our algorithms and models, and tweaking them to make sure they continue to be accurate. This task has been automated to the greatest extent it can be already. They are deeply hesitant to let Copilot automate it even more, because Copilot cannot think and render judgments, and thinking and rendering judgments is what we sell.

They would love if it it could automate shit like "contact various municipal authorities to get their publicly-available data on disasters in their area" but it actually can't; or rather, they don't trust it to do so. Early attempts to try and train it on this have produced results that are sufficiently variable and require so much human cross-checking as to not be worth it. And even if it COULD do that, analyzing that information is a whole other deal.

So that's one barrier. But the main barrier, the BIG one?

We are to a great extent legally responsible for the information we convey to our customers. Our recommendations for customers that make use of our more in-depth services to them aren't protected in this way; we've been wrong before, often to the tune of hundreds of millions of dollars. And we'll be wrong again! Our customers have no recourse on "we thought this was a good idea but it wasn't."

But we are absolutely liable that the data we base those wrong conclusions on has been crunched and analyzed and sourced in the ways we are contractually obligated to do so. Our work is warranted.

For our tax services, that goes one step further. Tax services are serious fucking business. The tax services we provide expose us not just to angry customers walking away or potentially suing us, they expose us to actual-factual criminal liability in the case of certain screwups. That information has to be gathered, stored, and processed properly. We can and have automated a lot of that. But the actual work work there is done by humans. Those humans use analytical tools, some quite powerful, but the work needs to attach to a human whose ass is on the line.

So far nobody whose ass is on the line has been willing to entrust much of this to Copilot.

That's what it comes down to for just about everything. The upper management folks are big-picture guys who look at LLMs and are dazzled by the possibilities. The line workers, like myself (I'm in a technology support role) basically don't get a say and largely don't care, they do what they're told with what they have.

But the specialists and middle-managers? Those are the guys whose name is on the work and who get in trouble if it isn't done properly. Those specialists are professionals in their fields often with many years of experience, and the tax guys in particular are sharp. Those middle-managers have the job of telling the UPPER management folks when they're off the rails and they cannot, if acting as directed, guarantee that our work will be warranted and not expose us to legal liability, and that's something upper management actually does pay attention to.

Does this mean the business side can't get use out of LLMs? No, of course not. But it does mean that they can't utterly transform the business based on what LLMs can do. What they provide is the easing of a lot of basic clerical work and that's it.

This is probably not worth the immense sums of money dumped into LLMs, or what we're paying for Copilot.

It's liability. These LLMs are just tools. They can't be held accountable, not for anything. When a tool is used, and things go badly wrong, you hold accountable the person using the tool. You can't indict a shovel; you CAN indict a guy for using a shovel to beat a man to death.

And again, we're an ideal use-case scenario and this is the barrier we're running up against.

Now, I'm sure there are companies that are going "fuck all this" and just charging ahead with LLMs anyway. That's absolutely happening.

A bunch of those guys are gonna go to jail, and when they're hauled away they're gonna bleat "It wasn't me, I just did what the machine said!"

If anyone wants to know why every tech company in the world right now is clamoring for AI like drowned rats scrabbling to board a ship, I decided to make a post to explain what's happening.

(Disclaimer to start: I'm a software engineer who's been employed full time since 2018. I am not a historian nor an overconfident Youtube essayist, so this post is my working knowledge of what I see around me and the logical bridges between pieces.)

Okay anyway. The explanation starts further back than what's going on now. I'm gonna start with the year 2000. The Dot Com Bubble just spectacularly burst. The model of "we get the users first, we learn how to profit off them later" went out in a no-money-having bang (remember this, it will be relevant later). A lot of money was lost. A lot of people ended up out of a job. A lot of startup companies went under. Investors left with a sour taste in their mouth and, in general, investment in the internet stayed pretty cooled for that decade. This was, in my opinion, very good for the internet as it was an era not suffocating under the grip of mega-corporation oligarchs and was, instead, filled with Club Penguin and I Can Haz Cheezburger websites.

Then around the 2010-2012 years, a few things happened. Interest rates got low, and then lower. Facebook got huge. The iPhone took off. And suddenly there was a huge new potential market of internet users and phone-havers, and the cheap money was available to start backing new tech startup companies trying to hop on this opportunity. Companies like Uber, Netflix, and Amazon either started in this time, or hit their ramp-up in these years by shifting focus to the internet and apps.

Now, every start-up tech company dreaming of being the next big thing has one thing in common: they need to start off by getting themselves massively in debt. Because before you can turn a profit you need to first spend money on employees and spend money on equipment and spend money on data centers and spend money on advertising and spend money on scale and and and

But also, everyone wants to be on the ship for The Next Big Thing that takes off to the moon.

So there is a mutual interest between new tech companies, and venture capitalists who are willing to invest $$$ into said new tech companies. Because if the venture capitalists can identify a prize pig and get in early, that money could come back to them 100-fold or 1,000-fold. In fact it hardly matters if they invest in 10 or 20 total bust projects along the way to find that unicorn.

But also, becoming profitable takes time. And that might mean being in debt for a long long time before that rocket ship takes off to make everyone onboard a gazzilionaire.

But luckily, for tech startup bros and venture capitalists, being in debt in the 2010's was cheap, and it only got cheaper between 2010 and 2020. If people could secure loans for ~3% or 4% annual interest, well then a $100,000 loan only really costs $3,000 of interest a year to keep afloat. And if inflation is higher than that or at least similar, you're still beating the system.

So from 2010 through early 2022, times were good for tech companies. Startups could take off with massive growth, showing massive potential for something, and venture capitalists would throw infinite money at them in the hopes of pegging just one winner who will take off. And supporting the struggling investments or the long-haulers remained pretty cheap to keep funding.

You hear constantly about "Such and such app has 10-bazillion users gained over the last 10 years and has never once been profitable", yet the thing keeps chugging along because the investors backing it aren't stressed about the immediate future, and are still banking on that "eventually" when it learns how to really monetize its users and turn that profit.

The pandemic in 2020 took a magnifying-glass-in-the-sun effect to this, as EVERYTHING was forcibly turned online which pumped a ton of money and workers into tech investment. Simultaneously, money got really REALLY cheap, bottoming out with historic lows for interest rates.

Then the tide changed with the massive inflation that struck late 2021. Because this all-gas no-brakes state of things was also contributing to off-the-rails inflation (along with your standard-fare greedflation and price gouging, given the extremely convenient excuses of pandemic hardships and supply chain issues). The federal reserve whipped out interest rate hikes to try to curb this huge inflation, which is like a fire extinguisher dousing and suffocating your really-cool, actively-on-fire party where everyone else is burning but you're in the pool. And then they did this more, and then more. And the financial climate followed suit. And suddenly money was not cheap anymore, and new loans became expensive, because loans that used to compound at 2% a year are now compounding at 7 or 8% which, in the language of compounding, is a HUGE difference. A $100,000 loan at a 2% interest rate, if not repaid a single cent in 10 years, accrues to $121,899. A $100,000 loan at an 8% interest rate, if not repaid a single cent in 10 years, more than doubles to $215,892.

Now it is scary and risky to throw money at "could eventually be profitable" tech companies. Now investors are watching companies burn through their current funding and, when the companies come back asking for more, investors are tightening their coin purses instead. The bill is coming due. The free money is drying up and companies are under compounding pressure to produce a profit for their waiting investors who are now done waiting.

You get enshittification. You get quality going down and price going up. You get "now that you're a captive audience here, we're forcing ads or we're forcing subscriptions on you." Don't get me wrong, the plan was ALWAYS to monetize the users. It's just that it's come earlier than expected, with way more feet-to-the-fire than these companies were expecting. ESPECIALLY with Wall Street as the other factor in funding (public) companies, where Wall Street exhibits roughly the same temperament as a baby screaming crying upset that it's soiled its own diaper (maybe that's too mean a comparison to babies), and now companies are being put through the wringer for anything LESS than infinite growth that Wall Street demands of them.

Internal to the tech industry, you get MASSIVE wide-spread layoffs. You get an industry that used to be easy to land multiple job offers shriveling up and leaving recent graduates in a desperately awful situation where no company is hiring and the market is flooded with laid-off workers trying to get back on their feet.

Because those coin-purse-clutching investors DO love virtue-signaling efforts from companies that say "See! We're not being frivolous with your money! We only spend on the essentials." And this is true even for MASSIVE, PROFITABLE companies, because those companies' value is based on the Rich Person Feeling Graph (their stock) rather than the literal profit money. A company making a genuine gazillion dollars a year still tears through layoffs and freezes hiring and removes the free batteries from the printer room (totally not speaking from experience, surely) because the investors LOVE when you cut costs and take away employee perks. The "beer on tap, ping pong table in the common area" era of tech is drying up. And we're still unionless.

Never mind that last part.

And then in early 2023, AI (more specifically, Chat-GPT which is OpenAI's Large Language Model creation) tears its way into the tech scene with a meteor's amount of momentum. Here's Microsoft's prize pig, which it invested heavily in and is galivanting around the pig-show with, to the desperate jealousy and rapture of every other tech company and investor wishing it had that pig. And for the first time since the interest rate hikes, investors have dollar signs in their eyes, both venture capital and Wall Street alike. They're willing to restart the hose of money (even with the new risk) because this feels big enough for them to take the risk.

Now all these companies, who were in varying stages of sweating as their bill came due, or wringing their hands as their stock prices tanked, see a single glorious gold-plated rocket up out of here, the likes of which haven't been seen since the free money days. It's their ticket to buy time, and buy investors, and say "see THIS is what will wring money forth, finally, we promise, just let us show you."

To be clear, AI is NOT profitable yet. It's a money-sink. Perhaps a money-black-hole. But everyone in the space is so wowed by it that there is a wide-spread and powerful conviction that it will become profitable and earn its keep. (Let's be real, half of that profit "potential" is the promise of automating away jobs of pesky employees who peskily cost money.) It's a tech-space industrial revolution that will automate away skilled jobs, and getting in on the ground floor is the absolute best thing you can do to get your pie slice's worth.

It's the thing that will win investors back. It's the thing that will get the investment money coming in again (or, get it second-hand if the company can be the PROVIDER of something needed for AI, which other companies with venture-back will pay handsomely for). It's the thing companies are terrified of missing out on, lest it leave them utterly irrelevant in a future where not having AI-integration is like not having a mobile phone app for your company or not having a website.

So I guess to reiterate on my earlier point:

Drowned rats. Swimming to the one ship in sight.

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starseedfxofficial · 2 hours ago

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The Secret Sauce of USDCAD Swing Trading Ever tried to bake a cake and realized you’re missing a key ingredient, like baking powder? That’s what happens when you swing trade without understanding market conditions. USDCAD is highly sensitive to changes in the price of oil and the divergence between the U.S. and Canadian economic outlooks. This means you’ve got to be smart—not just technically proficient, but also macro-savvy. Here's how to bake that profitable swing trading cake: - Know Your Trends Like You Know Your Coffee Preferences: Before you start, always check for overarching trends. Is the USD flexing its muscles like a bodybuilder at the Fed meeting, or is the CAD feeling feisty thanks to higher oil prices? Identifying these trends is crucial. Think of it like ordering your coffee—knowing whether you need a robust espresso shot (bullish USD) or a smooth flat white (strong CAD) will determine what’s on the trading menu. - Look for Divergence… The Fun Kind: USDCAD loves nothing more than when the fundamentals diverge. We’re talking about situations where the U.S. looks like it’s ready to hike rates, while the Canadian economy's outlook remains as soggy as last week's toast. Spotting these shifts ahead of the market is like finding a $20 bill in an old pair of jeans—it’s a feel-good moment that translates to big pips in your favor. - Underground Tactic: Currency Correlations: Here's where we get ninja-level. Most traders stick to basic chart analysis, but the real swing traders look at correlations. CAD is highly correlated to the price of oil. If crude prices are rallying, chances are CAD will too. Knowing this, you can time your USDCAD swings far better—when oil spikes, it's usually time for USDCAD to start dancing too. Don't just use traditional indicators—be smarter and tap into these unconventional data points. Timing the Market Like a Pro Swing trading USDCAD is a lot like surfing—you have to paddle out before the wave forms. Waiting too long means you're left splashing around, trying to catch something that's already breaking. Timing those swings is all about finding the right balance between momentum and reversal signals. - Moving Averages Are Your Lifeguard: A lot of pros swear by the 50-day and 200-day moving averages when swing trading USDCAD. The crossover between these two can indicate whether the seesaw is tilting in favor of buying or selling. But here’s a trick: don’t just blindly trade the crossovers. Wait for confirmation! Think of it as someone yelling "shark" at the beach—better make sure it’s not just a shadow before you freak out. - MACD Magic with a Twist: The MACD (Moving Average Convergence Divergence) is a classic tool, but don’t just settle for the default settings. Use a slower setting—like adjusting your MACD to 20, 50, 9—for a more accurate read of trends in a slower-moving pair like USDCAD. Think of it as wearing polarized sunglasses: everything gets just a bit clearer, and you can cut through the glare of market noise. - Fibonacci and Patience: Yes, I know—Fibonacci can seem like something only Leonardo da Vinci could understand, but applying it to the swing lows and highs can be like discovering the ultimate shortcut to grandma’s house. Use the Fibonacci retracement to help gauge potential entry points and expect reversals at the 50% and 61.8% levels. It’s like knowing exactly where the best waves form so you can be right there when it happens. A Different Approach to Risk Management Swing trading USDCAD without proper risk management is like jumping into a hot tub without checking the temperature—it could end up scalding you. Most traders get it wrong by focusing only on how much profit they want, rather than on how much risk they’re taking. Here’s how to avoid that rookie mistake: - Trade Small, Win Big: The truth is, many swing traders fail because they go in too big. Instead, think about position sizing as a means to let you survive through volatility. You wouldn’t try to drink an entire pitcher of margaritas in one gulp, right? Same goes for trades—small sips are better for your health. - Use the Smart Trading Tool: If you’re a stickler for precision, use our Smart Trading Tool to help with automated lot size calculations. It’s like having a safety net when you’re walking on a high wire—suddenly, everything seems less daunting. The Psychology of the Swing Trader Trading is as much about psychology as it is about numbers. Most traders get emotional, and that’s what leads to mistakes like pulling out early or, worse, revenge trading after a loss. Let’s break it down with a few examples. - Mastering Emotional Balance: Trading USDCAD can often make you feel like you're in a long-distance relationship. Just when you think things are stable, a central bank decision throws you off completely! The key is to stay level-headed. Don’t let fear drive you out or greed lure you in deeper. - Avoid the Common Pitfalls: One mistake many traders make is relying solely on technicals without considering the fundamentals. Treat USDCAD like an old friend—you have to understand why they act the way they do before you react. Sometimes they’re moody because of economic data, sometimes it's because oil’s acting up. - Join a Community of Swing Enthusiasts: Swing trading can be isolating, and there's nothing worse than feeling like you're out there swinging alone (pun intended). Join the StarseedFX Community, where you can share ideas, get feedback, and even laugh at those "oops, I hit 'sell' instead of 'buy'" moments. Remember, we all have them. Swing with Confidence, Not Recklessness Mastering swing trading for USDCAD is a game of precision, patience, and above all, preparation. By understanding the intricacies of currency correlations, the timing of moving averages, and managing your risk like a true pro, you’ll be better prepared to ride those market waves without getting wiped out. And hey, if you’re feeling lost, don’t forget—the journey to becoming a great swing trader is paved with a lot of small wins and a few bruises. Be humble, be willing to learn, and above all else, don't forget to laugh off your mistakes (because they're going to happen). After all, trading’s a lot more fun when you’re smiling—especially when your swings hit their targets. —————– Image Credits: Cover image at the top is AI-generated Read the full article

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flivv-developers · 4 days ago

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Return on Investment is every investor’s goal. An investor simply does not decide to pitch in their finances into something and expect no returns. Every investor does an equal amount of research and scrutiny before investing. As the savings and income of an individual are precious, money is supposed to grow and benefit the investor so he can seamlessly liquidate it later at profitable prices.

The chronology for getting ROI is simple. You invest Your money grows You liquidate it at the earliest

And as simple as it looks, some investments are subjected to market risks as well. However, An asset class like real estate is regarded as stable, especially in a volatile market. Real estate returns have averaged 11.6% per year in the last ten years, according to the Reserve Bank of India’s House Price Index, which tracks home prices in 10 major cities. In the past decade, this has outperformed both the equity market at 11% and gold at 8.8%.

Return On Investment Opportunity in the Upcoming Developing Areas

Hyderabad Pharma City will be the World’s Largest Pharma City on 20,000 acres, which will include Pharma University, R&D Centers, Manufacturing, and Township inclusion. So far, the infrastructural development present around the area is a 200 ft main road and Amazon data center. The big companies like Novartis, Dr. Reddy’s, and even Austrak will be setting up their facilities by 2025. Considering the massive development in an area where innovation and infrastructure will work together, it is no less than a massive breakthrough for Telangana. Therefore, investing in that area in the initial stages will reap benefits like the present Hitech City. With the availability of multiple venture options there, the choices for your investments will be wider.

Ventures on the main road of Hyderabad Pharma City have higher chances of return on investments because the commercial roadway passing through the ventures will have more effective appreciation. The demand and sales of the commercial properties will be higher than compared to the properties that are inside or in the 4-6th bit of the road. So the availability of properties will narrow down because most of the buyers will opt for the ones situated on the main road. The early buyers will only reap the benefits and will be able to resell at profitable prices easily.

There was a time when Hitech city was in a similar condition, and people would hardly consider investing there saying, “it’s too far” or that there’s no future. But guess what?

The West of Hyderabad (present Hitech City) is the most premium area in all of Hyderabad to secure investments. The ticket prices are too high and not affordable for first-time investors to begin their Investment journey.

To conclude, the Hyderabad Pharma City doesn’t require much of a ticket price as it is super affordable presently. The main road has already been constructed, the electricity grids are installed, and the Amazon Data Center has set up its data center in Mirkhanpet village. Following these developments, the number of open land ventures will increase, and so will the investments. The infrastructure will nurture, and so will the prices!

At Flivv Developers, we suggest the best ROI Options for you. Our project, NS Homes, is located on the 200 ft main road of the Pharma City has got a lot of potential as it is located on the first bit of the main road. The commercial road will have suitable development, and the prices, and land value appreciation will be according to the location’s progress with time. Which will in return provide you with the best Return on Investment.

#real estate investing #real estate marketing #open plots #property for buying

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smgoi · 20 days ago

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How Machine Learning Models Are Trained

Imagine teaching a child to identify animals. You might show them pictures, point out features, and explain patterns. Over time, they learn to recognize animals on their own. Training a machine learning (ML) model works similarly. By exposing it to lots of data and guiding it through patterns, we teach it to "learn" and make decisions.

The Training Process: How Do Machines Learn?

To train a machine learning model, we follow a few critical steps:

Data Collection: Gathering relevant data for the model.

Data Preprocessing: Cleaning and preparing the data for analysis.

Choosing a Model: Selecting the type of model (like a neural network or decision tree) based on the task.

Training: Teaching the model by feeding it data.

Evaluation: Testing the model to see how well it performs.

Tuning: Adjusting the model for better accuracy.

Let’s dive into each of these steps!

Step 1: Data Collection

Data is the fuel for any machine learning model. The data used depends on the goal:

Images for a model that identifies objects.

Text for a model that translates languages.

Numbers for a model predicting stock prices.

The quality of data is crucial. Inaccurate or biased data leads to poor predictions. For example, if a face recognition model only trains on images of adults, it might struggle to recognize children.

Real-World Example: Suppose we're building a model to classify emails as spam or not spam. Our dataset would need a mix of spam and legitimate emails. Each email will include various features like words, sender, and formatting.

Step 2: Data Preprocessing

Raw data often contains errors, missing values, or noise. Data preprocessing cleans this up so the model can focus on learning. This step may involve:

Removing errors (like duplicates or incorrect entries)

Filling in missing values

Normalizing the data (scaling numbers to make them comparable)

In our spam email example, preprocessing could include converting all words to lowercase, removing special characters, or removing common words like “the” or “and” that don’t contribute much to identifying spam.

Step 3: Choosing the Right Model

Choosing a machine learning model is like selecting the right tool for a job. Here are a few types:

Linear Regression: Great for predicting numerical values (e.g., house prices).

Decision Trees: Works well for classification tasks, like spam detection.

Neural Networks: Powerful for complex tasks like image recognition and natural language processing.

Each model has strengths and weaknesses, and the choice depends on the type of data and the problem being solved. In our spam detector, a decision tree model might be a good fit, as it can create "branches" to separate spam and non-spam emails based on patterns.

Step 4: Training

Once the data is prepared and the model is selected, it’s time to train the model. Here’s how it works:

Splitting the Data: The data is split into two parts—training data and test data. The training data helps the model learn, while the test data evaluates how well it has learned.

Feeding Data in Batches: The training data is given to the model in small portions, or batches, to avoid overwhelming it and to help it learn progressively.

Adjusting Weights: The model starts with random "weights," which determine how much importance it assigns to different features in the data. With each batch, it adjusts these weights to improve accuracy.

Loss Function: After each batch, the model calculates its “loss,” or how far off its predictions are. The goal is to reduce this loss by adjusting weights until it makes accurate predictions.

Real-World Example: In spam detection, the model initially guesses which emails are spam. If it’s wrong, it adjusts its “weights” to better understand the differences, like noting that phrases like “free money” might indicate spam.

Step 5: Evaluation

Once trained, it’s time to test the model with the test data. This data is new to the model and lets us see if it can make correct predictions.

Key Evaluation Metrics

Accuracy: Percentage of correct predictions.

Precision: Percentage of true positive predictions among all positive predictions (important in spam detection).

Recall: Percentage of true positive predictions among actual positive instances.

In our spam example, high precision ensures the model doesn’t incorrectly mark non-spam emails as spam, and high recall ensures it catches all spam emails.

Step 6: Tuning the Model

After evaluating, there’s almost always room for improvement. Model tuning involves adjusting parameters or experimenting with different models to improve performance.

Techniques for Tuning

Hyperparameter Tuning: Adjusts factors like batch size, learning rate, and number of layers in a neural network.

Cross-Validation: Splits the data into multiple sections and trains the model on each, ensuring it performs well on all parts of the dataset.

In our example, if the spam detector is letting too many spam emails through, we could tune its parameters or try a different algorithm to boost accuracy.

Challenges in Training Machine Learning Models

While training machine learning models is powerful, it comes with challenges:

Overfitting: When a model performs too well on training data but fails with new data.

Bias in Data: Biased data leads to biased models, affecting predictions.

Computational Resources: Training complex models like neural networks requires powerful hardware, which can be costly.

Real-World Impact: Where Machine Learning Training is Used

Machine learning is behind many tools we use daily, from personalized recommendations on streaming platforms to fraud detection in banking. Training quality models has transformative power across industries, including healthcare, finance, and education.

In Education: At St. Mary’s, students studying AI and Computer Science learn about these processes, preparing for careers where machine learning continues to grow in importance.

Conclusion

The process of training machine learning models is both challenging and rewarding. As we gather more data and develop better algorithms, models become more accurate and capable. For students at St Mary's Group of Institutions, Best Engineering Colleges in Hyderabad, mastering these concepts opens the door to exciting opportunities in fields like AI and data science.

With a solid understanding of how Artificial Intelligence and Machine Learning models are trained, students are better equipped to contribute to tomorrow’s technological advancements. Embrace the journey—it’s how the next generation of AI experts begins!

#best btech colleges in india #btech course #ai #artificial intelligence

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things-about-cars-in-posts · 1 year ago

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Welcome to Replying To Replies, the show where I absent-mindedly scroll through replies until I rack up enough things to say to write a huge post and probably have it removed for tag spam!

In this episode, @kawaiipinkbunny wonders "if it’s consumer, manufacturer, or dealership driven change? It’s certainly easier to only sell cars in 3 basic colors and just make your customers accept it". And indeed it's a vicious circle between all of them: "dealers fill their lots with colors that the widest variety of customers will settle for… so black, white and silver/gray" ¹, and since "most people buy whatever is on the lot, very few custom order anymore" ¹, what will happen is dealerships will see high sales of those colors and manufacturers will see high orders for those colors, leading them to lean into those colors even harder.

Indeed, many report as much - e.g."recent personal experience is that I bought a black car (which I didn't want…again) because it was what they had in stock and choosing another colour [...] would cost an absurd lot more" ².

And indeed, a lot of appreciation for actual colors can be found in the replies, from making it "easier to spot my ride" ³ to feeling "safer in poor visibility" ⁴ as "data does support that brightly coloured cars aren't involved in collisions as often" ⁵, in stark contrast with the idea that the chart above represents popularity among consumers.

@toastedpopsicle writes: "this is a similar phenomenon to the blandification of interior and exterior home design, and happens for the same purpose; homes and vehicles are no longer meant to be personal possessions, they're intended to be readily resold sources of equity. "Don't customize your home or car because that reduces the resale value" leads to "customers aren't interested in personable colors" and it continues as a feedback loop."

The point of resale value in particular was brought up many times ⁶ ⁷, and while having colors most people will settle for is even more important for dealers when they are ordering cars for leasing (a form of long-term renting) I'd like us consumers to be aware that greyscale cars retaining the most resale value is not even true! You know what color retains the most resale value, by a huge margin? YELLOW. Because someone will pay more for a rare bright color, no one will pay more for the omnipresent grayscale. What now? Oh and also YOU OWN THE FUCKING THING!!! It usually takes a house to top it as the biggest personal purchase of your life and the personal space you spend the most time in, and you're going to decorate it according to the imaginary tastes of an imaginary buyer on the off-chance it can actually earn you a fraction of the kind of money you'll gleefully spend on decorating a room?!

I am calm.

Although, of course, it's also a matter of the premium this system leads other colors to command, as too many to list pointed out. (Fun fact: when Porsche couldn't keep up with demand for its Paint To Sample program, where you could bring them any sample and they'd paint your car to match, they raised prices to lower demand - but since this made it seem more prestigious demand increased.)

If you can't afford that premium, my honest advice is: buy used! And I don't mean "Can't find your color on the lot? Look in the used market!", I mean that if you are in the kind of financial situation where you really can't afford, or at least justify, a $x00 premium on a car to have it look how you want, it probably means you could really benefit from the big savings that inherently come from buying used. There's more of a process to it and it requires more precautions, but compare savings and work involved and it will look a lot more appealing than your job. And remember, if you can't be comfortable buying that car at 3 years old, that's not a car you want at all!

Another trend seen in the replies, however, is people who actually like greyscale colors, be it because they "blend in better so you are less likely to get pulled over" ⁸ ⁹ ¹⁰ ¹¹ or because "black doesn't look dirty as quickly" ¹² or because "white cars are especially popular in hot regions" ¹² ¹³, or even just "murdered out cars are sexy I'm sorry" ¹⁴.

And to these people I want to say: there are still so many more options than greyscale.

Do you want a subtle car? There's also light green!

Do you want a car that won't get dirty so quick? There's also dark brown!

Do you want a light color? There's also light blue!

You want something that looks enticingly menacing? There's also dark purple!

I could go on for literal days. These are four picks from my "Nice Colors" list of over a hundred.

There is such a wealth of options that even most people who chose greyscale would have found something they liked more had they been exposed to them all.

And then those who would still pick something greyscale can actually appreciate their choice a lot more. Because maybe it's true that "shades aren't bland, you just don't know how to appreciate them" ¹⁵ (spoilers: no, many silvers are actually bland ass shades that don't compliment the cars they're on at all), but this RS6's menacing black is a shade you can appreciate in this picture...

...not in this one.

You cannot appreciate something when it's the only thing you see.

So even black and white lovers (which includes me! There are a couple cars in my wishlist I would get in those colors, including my favorite car ever!) will be happier in a more colored world, where their choices will have the chance to pop.

Also, as a post-scriptum, I wanted to shout out this fantastic comment on the Harlequin by aptly named @shameless0shenanigans:

"I SAW THIS CAR ON MY WAY TO CLASS EVERYDAY AND LOVED IT. I want something like it so if I'm ever taken to traffic court because "I didn't see their car" I can just show the jury my fucking clown car and ask "Are you sure about that?""

¹@delta-foxtrot ²@troubledthoughts

³@spooniepumpkin ⁴@secret-crow-syndicate

⁵@aralintheobsessive ⁶@min-haven-pokemon-sanctuary

⁷@bigkarlachenergy ⁸@mabswinterknight

⁹@rust-4-life ¹⁰@aetherology

¹¹@n0body1mportant ¹²@l1zriil

¹³@weirdfangirlblog ¹⁴@jhenaidah

¹⁵@gloomytk

Gradually getting more bland and cookie cutter

#does it show -does it show at all- that I have very strong feelings on this matter #colors

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