#AI for demand prediction
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How Can Data Science Predict Consumer Demand in an Ever-Changing Market?

In today’s dynamic business landscape, understanding consumer demand is more crucial than ever. As market conditions fluctuate, companies must rely on data-driven insights to stay competitive. Data science has emerged as a powerful tool that enables businesses to analyze trends and predict consumer behavior effectively. For those interested in mastering these techniques, pursuing an AI course in Chennai can provide the necessary skills and knowledge.
The Importance of Predicting Consumer Demand
Predicting consumer demand involves anticipating how much of a product or service consumers will purchase in the future. Accurate demand forecasting is essential for several reasons:
Inventory Management: Understanding demand helps businesses manage inventory levels, reducing the costs associated with overstocking or stockouts.
Strategic Planning: Businesses can make informed decisions regarding production, marketing, and sales strategies by accurately predicting consumer preferences.
Enhanced Customer Satisfaction: By aligning supply with anticipated demand, companies can ensure that they meet customer needs promptly, improving overall satisfaction.
Competitive Advantage: Organizations that can accurately forecast consumer demand are better positioned to capitalize on market opportunities and outperform their competitors.
How Data Science Facilitates Demand Prediction
Data science leverages various techniques and tools to analyze vast amounts of data and uncover patterns that can inform demand forecasting. Here are some key ways data science contributes to predicting consumer demand:
1. Data Collection
The first step in demand prediction is gathering relevant data. Data scientists collect information from multiple sources, including sales records, customer feedback, social media interactions, and market trends. This comprehensive dataset forms the foundation for accurate demand forecasting.
2. Data Cleaning and Preparation
Once the data is collected, it must be cleaned and organized. This involves removing inconsistencies, handling missing values, and transforming raw data into a usable format. Proper data preparation is crucial for ensuring the accuracy of predictive models.
3. Exploratory Data Analysis (EDA)
Data scientists perform exploratory data analysis to identify patterns and relationships within the data. EDA techniques, such as data visualization and statistical analysis, help analysts understand consumer behavior and the factors influencing demand.
4. Machine Learning Models
Machine learning algorithms play a vital role in demand prediction. These models can analyze historical data to identify trends and make forecasts. Common algorithms used for demand forecasting include:
Linear Regression: This model estimates the relationship between dependent and independent variables, making it suitable for predicting sales based on historical trends.
Time Series Analysis: Time series models analyze data points collected over time to identify seasonal patterns and trends, which are crucial for accurate demand forecasting.
Decision Trees: These models split data into branches based on decision rules, allowing analysts to understand the factors influencing consumer demand.
5. Real-Time Analytics
In an ever-changing market, real-time analytics becomes vital. Data science allows businesses to monitor consumer behavior continuously and adjust forecasts based on the latest data. This agility ensures that companies can respond quickly to shifts in consumer preferences.
Professionals who complete an AI course in Chennai gain insights into the latest machine learning techniques used in demand forecasting
Why Pursue an AI Course in Chennai?
For those looking to enter the field of data science and enhance their skills in predictive analytics, enrolling in an AI course in Chennai is an excellent option. Here’s why:
1. Comprehensive Curriculum
AI courses typically cover essential topics such as machine learning, data analysis, and predictive modeling. This comprehensive curriculum equips students with the skills needed to tackle real-world data challenges.
2. Hands-On Experience
Many courses emphasize practical, hands-on learning, allowing students to work on real-world projects that involve demand forecasting. This experience is invaluable for building confidence and competence.
3. Industry-Relevant Tools
Students often learn to use industry-standard tools and software, such as Python, R, and SQL, which are essential for conducting data analysis and building predictive models.
4. Networking Opportunities
Enrolling in an AI course in Chennai allows students to connect with peers and industry professionals, fostering relationships that can lead to job opportunities and collaborations.
Challenges in Predicting Consumer Demand
While data science offers powerful tools for demand forecasting, organizations may face challenges, including:
1. Data Quality
The accuracy of demand predictions heavily relies on the quality of data. Poor data quality can lead to misleading insights and misguided decisions.
2. Complexity of Models
Developing and interpreting predictive models can be complex. Organizations must invest in training and resources to ensure their teams can effectively utilize these models.
3. Rapidly Changing Markets
Consumer preferences can shift rapidly due to various factors, such as trends, economic changes, and competitive pressures. Businesses must remain agile to adapt their forecasts accordingly.
The curriculum of an AI course in Chennai often includes hands-on projects that focus on real-world applications of predictive analytics
Conclusion
Data science is revolutionizing how businesses predict consumer demand in an ever-changing market. By leveraging advanced analytics and machine learning techniques, organizations can make informed decisions that drive growth and enhance customer satisfaction.
For those looking to gain expertise in this field, pursuing an AI course in Chennai is a vital step. With a solid foundation in data science and AI, aspiring professionals can harness these technologies to drive innovation and success in their organizations.
#predictive analytics#predictivemodeling#predictiveanalytics#predictive programming#consumer demand#consumer behavior#demand analysis#machinelearning#machine learning#technology#data science#ai#artificial intelligence#Data science course#AI course#AI course in Chennai#Data science course in Chennai#Real-Time Analytics#Data Collection#Data Cleaning
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Strengthening Foundations:
Navigating Customer Demands and Expectations for Robust Trucking Relationships Type your email… Subscribe The trucking industry stands as a pivotal pillar in the global supply chain, its wheels turning the gears of economy and commerce. Yet, amidst its crucial role, trucking companies face the perpetual challenge of balancing customer demands and expectations with operational efficiency and…
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#"AI trucking industry"#"blockchain in logistics"#"competitive pricing trucking"#"competitive trucking services"#"CRM systems trucking"#"customer relationships trucking"#"customer retention trucking"#"customer satisfaction trucking"#"customer service in trucking"#"data analytics in trucking"#"eco-friendly trucking"#"green trucking solutions"#"IoT devices trucking"#"loyalty programs trucking"#"personalized logistics solutions"#"predictive analytics trucking"#"real-time shipment tracking"#"secure trucking transactions"#"sustainable trucking practices"#"technology in trucking"#"trucking industry customer demands"#"trucking industry innovation"#"trucking industry trends"#"trucking service customization"#"value-added trucking services"#business#cash flow management#Freight#freight industry#Freight Revenue Consultants
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Stuff about American election night that you should know:
We’re one week out! Crazy. So I know too much about US politics because I explain this for money, so I figured it might be helpful to talk a bit about what we should expect from election night. If you're not American, are new to our insane election system, or are anxious about what's happening next week, here's the deal with next Tuesday:
1. Most important thing: Do NOT expect to know the winner on election night. Different states have different laws about when they can start counting early/mail-in votes, which often slows down reporting time.
2020 took until the Saturday after to call because of the high mail-in vote count due to Covid, and while that isn't happening this time, it'll take longer than 2016, 2012, or 2008 because the polls are predicting that this one's going to be a lot closer than those. Consider just going to bed instead of staying up for the results.
2. Because of the Electoral College, popular vote doesn't matter as much as who wins each individual state does. Every state has a certain amount of electoral votes based on population, whoever wins a state gets all their votes, whoever gets to 270/538 wins. We know how most states are going to vote. The Electoral College puts the election in the hands of 7 "swing" states that could go either way. This time, that's Pennsylvania, Georgia, North Carolina, Michigan, Wisconsin, Arizona, and Nevada. These are the states to watch. Here's the map:
3. No one will know anything until polls close and states start reporting results. Doomscrolling is kind of pointless anyways, but it's especially pointless before 7pm. here's a map of closure times:

4. Data will shift throughout the night. Rural counties report results first because fewer people live there. This means the earlier you check, the more conservative the state maps might look. Do not look at the election results for any state with less than 90% reporting and freak out, especially if the state hasn't been called (deemed mathematically impossible for the other candidate to win) by multiple news outlets.
5. Voter fraud happens way less than you think it does. Pretty much never, actually. One study claims you're more likely to get struck by lightning than you are to witness actual, impersonation-based voter fraud in a modern US election. Be extremely skeptical of any voter fraud claims you might see.
6. Avoid getting news from social media accounts that aren't news outlets. There's a lot of disinformation out there, especially as AI/Deepfake tech is getting worse. Fact-check everything you might see. Anyone can make a destiel meme about the election. make sure it's true before you reblog it.
7. The electoral college sucks shit and does allow for a 269-269 vote tie. In this case, it goes to the House of Representatives, who are majority-Republican and will pick Trump. Some states might be within 1% (like 49.3%-49.7%) and candidates can demand recounts, which might delay official results by weeks or months. It HAS to be over by mid- December when the Electoral College officially votes.
8. take care of yourselves. if we're not going to know on election night, you may as well power down your phone and go to bed at a reasonable hour.
#Linked a bunch of articles throughout if you want more info.#us politics#election 2024#i am not looking forward to it. but the only way out is through.
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The reason I took interest in AI as an art medium is that I've always been interested in experimenting with novel and unconventional art media - I started incorporating power tools into a lot of my physical processes younger than most people were even allowed to breathe near them, and I took to digital art like a duck to water when it was the big, relatively new, controversial thing too, so really this just seems like the logical next step. More than that, it's exciting - it's not every day that we just invent an entirely new never-before-seen art medium! I have always been one to go fucking wild for that shit.
Which is, ironically, a huge part of why I almost reflexively recoil at how it's used in the corporate world: because the world of business, particularly the entertainment industry, has what often seems like less than zero interest in appreciating it as a novel medium.
And I often wonder how much less that would be the case - and, by extension, how much less vitriolic the discussion around it would be, and how many fewer well-meaning people would be falling for reactionary mythologies about where exactly the problems lie - if it hadn't reached the point of...at least an illusion of commercial viability, at exactly the moment it did.
See, the groundwork was laid in 2020, back during covid lockdowns, when we saw a massive spike in people relying on TV, games, books, movies, etc. to compensate for the lack of outdoor, physical, social entertainment. This was, seemingly, wonderful for the whole industry - but under late-stage capitalism, it was as much of a curse as it was a gift. When industries are run by people whose sole brain process is "line-go-up", tiny factors like "we're not going to be in lockdown forever" don't matter. CEOs got dollar signs in their eyes. Shareholders demanded not only perpetual growth, but perpetual growth at this rate or better. Even though everyone with an ounce of common sense was screaming "this is an aberration, this is not sustainable" - it didn't matter. The business bros refused to believe it. This was their new normal, they were determined to prove -
And they, predictably, failed to prove it.
So now the business bros are in a pickle. They're beholden to the shareholders to do everything within their power to maintain the infinite growth they promised, in a world with finite resources. In fact, by precedent, they're beholden to this by law. Fiduciary duty has been interpreted in court to mean that, given the choice between offering a better product and ensuring maximum returns for shareholders, the latter MUST be a higher priority; reinvesting too much in the business instead of trying to make the share value increase as much as possible, as fast as possible, can result in a lawsuit - that a board member or CEO can lose, and have lost before - because it's not acting in the best interest of shareholders. If that unsustainable explosive growth was promised forever, all the more so.
And now, 2-3-4 years on, that impossibility hangs like a sword of Damocles over the heads of these media company CEOs. The market is fully saturated; the number of new potential customers left to onboard is negligible. Some companies began trying to "solve" this "problem" by violating consumer privacy and charging per household member, which (also predictably) backfired because those of us who live in reality and not statsland were not exactly thrilled about the concept of being told we couldn't watch TV with our own families. Shareholders are getting antsy, because their (however predictably impossible) infinite lockdown-level profits...aren't coming, and someone's gotta make up for that, right? So they had already started enshittifying, making excuses for layoffs, for cutting employee pay, for duty creep, for increasing crunch, for lean-staffing, for tightening turnarounds-
And that was when we got the first iterations of AI image generation that were actually somewhat useful for things like rapid first drafts, moodboards, and conceptualizing.
Lo! A savior! It might as well have been the digital messiah to the business bros, and their eyes turned back into dollar signs. More than that, they were being promised that this...both was, and wasn't art at the same time. It was good enough for their final product, or if not it would be within a year or two, but it required no skill whatsoever to make! Soon, you could fire ALL your creatives and just have Susan from accounting write your scripts and make your concept art with all the effort that it takes to get lunch from a Star Trek replicator!
This is every bit as much bullshit as the promise of infinite lockdown-level growth, of course, but with shareholders clamoring for the money they were recklessly promised, executives are looking for anything, even the slightest glimmer of a new possibility, that just might work as a life raft from this sinking ship.
So where are we now? Well, we're exiting the "fucking around" phase and entering "finding out". According to anecdotes I've read, companies are, allegedly, already hiring prompt engineers (or "prompters" - can't give them a job title that implies there's skill or thought involved, now can we, that just might imply they deserve enough money to survive!)...and most of them not only lack the skill to manually post-process their works, but don't even know how (or perhaps aren't given access) to fully use the software they specialize in, being blissfully unaware of (or perhaps not able/allowed to use) features such as inpainting or img2img. It has been observed many times that LLMs are being used to flood once-reputable information outlets with hallucinated garbage. I can verify - as can nearly everyone who was online in the aftermath of the Glasgow Willy Wonka Dashcon Experience - that the results are often outright comically bad.
To anyone who was paying attention to anything other than please-line-go-up-faster-please-line-go-please (or buying so heavily into reactionary mythologies about why AI can be dangerous in industry that they bought the tech companies' false promises too and just thought it was a bad thing), this was entirely predictable. Unfortunately for everyone in the blast radius, common sense has never been an executive's strong suit when so much money is on the line.
Much like CGI before it, what we have here is a whole new medium that is seldom being treated as a new medium with its own unique strengths, but more often being used as a replacement for more expensive labor, no matter how bad the result may be - nor, for that matter, how unjust it may be that the labor is so much cheaper.
And it's all because of timing. It's all because it came about in the perfect moment to look like a life raft in a moment of late-stage capitalist panic. Any port in a storm, after all - even if that port is a non-Euclidean labyrinth of soggy, rotten botshit garbage.
Any port in a storm, right? ...right?
All images generated using Simple Stable, under the Code of Ethics of Are We Art Yet?
#ai art#generated art#generated artwork#essays#about ai#worth a whole 'nother essay is how the tech side exists in a state that is both thriving and floundering at the same time#because the money theyre operating with is in schrodinger's box#at the same time it exists and it doesnt#theyre highly valued but usually operating at a loss#that is another MASSIVE can of worms and deserves its own deep dive
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AlphaFold Nobel Prize!
Hey everyone :) this isn't a structure, but there is some protein news that is pretty relevant to this blog that I felt I had to share. This article gives a nice overview of AI-predicted protein structures and what sorts of things they can do for research. It's not too long, and I recommend taking a look
If you've been seeing my posts for any amount of time, I've absolutely given you a flawed view of how useful AF can be. Experimentally determining protein structures is a demanding and difficult process (I've never done it, but I've learned the overview of how x ray crystallography works, and I can only imagine how much work it would take). AI-generated structures are not going to make structural biology obsolete, but they are massively helpful in making predictions that go on to guide further research.
While in many fields (especially creative areas like art and writing) AI has significant ethical concerns, I feel like this sort of use of AI in science is an overwhelmingly positive thing. The data used to train it is publicly available, and science works by building on the work done by those before us. Furthermore, while AI may not be great at generating new ideas or copying humans, it is very good at sorting large amounts of data and using it to make predictions. It's more akin to very complicated statistics than an attempt at the Turing test, and in this case it is a valuable tool to expand the ways we can do science!
#science#biochemistry#biology#chemistry#stem#proteins#protein structure#science side of tumblr#protein info
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AI and Donald Trump Are Watching You—And It Could Cost You Everything
Imagine this: You post your thoughts online. Or you express support for human rights. Or you attend a peaceful protest. Months later, you find yourself denied a visa, placed on a watchlist, or even under investigation—all because an algorithm flagged you as a ‘threat.’ This isn’t a dystopian novel. It’s happening right now in the U.S.
How AI Is Being Weaponized Against Protesters and Online Speech The Trump administration has rolled out AI-driven surveillance to monitor and target individuals based on their political beliefs and activities. According to reports, these systems analyze massive amounts of online data, including social media posts, protest attendance, and affiliations.
The goal? To identify and suppress dissent before it even happens.
Here’s what this means:
Attending a Protest Could Put You on a Government Watchlist – AI systems are being trained to scan for ‘suspicious behavior’ based on location data and social media activity.
Your Social Media History Can Be Used Against You – The government is using algorithms to flag people who express opinions that don’t align with Trump’s agenda.
Expressing Your Opinion Online Can Have Consequences – It’s not just about attending protests anymore. Simply posting criticism of the government, sharing articles, or even liking the ‘wrong’ post could get you flagged.
Dissenters Could Face Harsh Consequences – In some cases, simply supporting the wrong cause online could lead to visa denials, surveillance, or worse.
AI and Student Visa Bans: A Dangerous Precedent Recently, AI was used to screen visa applicants for supposed ‘Hamas support,’ leading to students being denied entry to the U.S. without due process. This is alarming for several reasons:
False Positives Will Ruin Lives – AI systems are not perfect. Innocent people will be flagged, denied entry, or even deported based on misinterpretations of their online activity.
This Can Be Expanded to Anyone – Today, it’s foreign students. Tomorrow, it could be U.S. citizens denied jobs, housing, or government services for expressing their political views.
It Sets a Dangerous Global Example – If the U.S. normalizes AI-driven political suppression, other governments will follow.
Marco Rubio’s ‘Catch and Revoke’ Plan: A New Threat Senator Marco Rubio has proposed the ‘Catch and Revoke’ plan, which would allow the U.S. government to scan immigrants’ social media with AI and strip them of their visas if deemed a ‘threat.’ This raises serious concerns about surveillance overreach and algorithm-driven repression, where immigrants could be punished for harmless or misinterpreted online activity. This policy could lead to:
Mass Deportations Based on AI Errors – Algorithms are prone to bias and mistakes, and immigrants may have no recourse to challenge these decisions.
Fear-Driven Self-Censorship – Many may feel forced to silence themselves online to avoid government scrutiny.
A Precedent for Broader Use – What starts with immigrants could easily be expanded to citizens, targeting dissenters and activists.
What’s at Stake?
The ability to speak freely, protest, and express opinions without fear of government retaliation is a fundamental right. If AI surveillance continues unchecked, America will become a place where thought crimes are punished, and digital footprints determine who is free and who is not.
The Bigger Picture
Technology that was meant to make life easier is now being turned against us. Today, it’s AI scanning protest footage. Tomorrow, it could be predictive policing, social credit systems, or AI-driven arrest warrants.
What Can You Do?
Be Mindful of Digital Footprints – Understand that what you post and where you go could be tracked.
Support Digital Rights Organizations – Groups like the ACLU and EFF are fighting against mass surveillance.
Demand Transparency – Governments must be held accountable for how they use AI and surveillance.
Freedom dies when people stop fighting for it. We must push back before AI turns democracy into an illusion.
Source:
https://www.fastcompany.com/91295390/how-the-trump-administration-plans-to-use-algorithms-to-target-protesters
#usa politics#politics#us politics#president trump#donald trump#trump administration#trump#trump is a threat to democracy#america#human rights#freedom of speech#free speech
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At this point I am really wondering how the entertainment industry, especially gaming industry, is going to uphold/maintain themselves.
One layoff after another. How are people from that industry supposed to find a new job there when layoffs are happening everywhere? Do studios really think there’s longevity when they aren’t even willing to hire newcomers/juniors so there‘s adequate supply in the work force? Because look at how it’s currently going: investors want more and more money, the workload increases, but people are getting fired, leaving a smaller team to do said work, even distributing them for 2 or 3 projects at the same time, only to crash in a burnout or in later years go into retirement. Then who’s left? AI? Are you kidding me? As if games aren’t becoming more and more repetitive anyway, because of some „safe recipe for good numbers“ strategy. Creativity and the people behind it are suffering.
It’s been almost 2 years since I saw a junior 3D character artist offer. Ever since then it’s been a desert. And it’s not looking all too bright in other departments either. It’s now even a thing in job descriptions where they want you to have „AI abilities“. So as a junior or regular they want you to feed their machine, so in a few years they can fire you. The audacity.
Another audacity are those layoffs just to rehire people for a smaller price (can’t tell me otherwise. For me this is a tactic to put pressure on the work force to say yes to less money otherwise they will stay jobless). People that made projects what they are today, who are seniors and leads for a reason, out of a job just like that. Make it make sense (it doesn’t).
Studios like ubisoft now openly saying that they want to focus on AI, like assets completely made by AI to „save time and money“ and expand AI onto more fields. Shame on them.
The way creative industries like gaming finance themselves is also their biggest poison. And I only see a solution in that by regulating investors demands and upper positions sheaningans. They can’t have „absolute power“ anymore. It’s destructive and greedy and not realistic. Games can not be linearly successful. For the game design „recipe“ to improve it needs iteration just like when you work in a project for example and work on a design that needs to be iterated until it‘s improved or solid even. We see time and time again that „business/numbers people“ and creatives do not go hand in hand. We see an extreme imbalance.
I would predict that with less creative new input and letting mainly AI do the work consumers will be less and less entertained because everything seems to be and look the same. It will stagnate. And then crumble. And the industry needs to start like it did before. And that’s what I guess for the big companies.
With the layoffs happening and not enough job offers in return I could see that big talents get together to build their own studios now and we may get an era of new successful and growing studios happening that may even replace the current triple A studios one day in the future. They may even change the financing game. We saw successful games happening through platforms like kickstarter more often. So it might lead back to a „power to the people“ thing. Having an idea for a project and seeing if enough people agree and invest to see it happening. There’s room for improvement in that system. That’s all what it leads back to; in the end the consumers need to be satisfied to make it a creative and monetary success. BG3 and larian studios was a good example for that. It’s what made coral island grow and grow too. So there‘s potential.
Feel free to comment your theories. I really would like to see what others think about the current state of gaming studios and how it will or could develop.
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So so curious.
🩸🩸🩸🩸🩸🩸🩸🩸🩸🩸🩸🩸
📸📸📸📸📸📸📸📸📸📸📸📸
🪷🪷🪷🪷🪷🪷🪷🪷🪷🪷🪷🪷
🔭🔭🔭🔭🔭🔭🔭🔭🔭🔭🔭🔭
Thanks 😊.
36 for 🩸
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This isn’t good. This really isn’t good. Bobby shouldn’t be here, listening to this. Is there another way out of this room? It’s a first floor, outside entry motel room. There’s no fire escape. He’s trapped. Too bad he’s not the sort of creature that can turn into a bat and fly away.
“I’m not sleeping with anyone else!” Buck insists. “I swear, Eddie! You have to believe me!”
Bobby hears Eddie scoff.
“Then what the hell are you doing Buck? What am I supposed to think?”
And Bobby has about two seconds to stop Buck from folding. He might have made Bobby promises, but he’s never been known to be logical when it comes to Eddie. Bobby had better-
“It’s Bobby,” Buck says.
Yep. Folded like paper. Not even printer stock. Receipt paper.
“What?” Eddie demands. Which makes sense. Why the hell would Eddie take that at face value?
“It’s Bobby,” Buck says again. “Bobby’s in the motel room. He broke out of his grave because he’s a vampire now. He’s also sort of behaving like a feral cat so I’m not allowed to tell you.”
“A feral cat?” Bobby can’t help but parrot angrily.
Which, he realizes a moment too late, only confirms everything Buck has just said. If he was going to figure out how to turn into a bat and fly away, he missed his moment.
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36 for📸
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“Yes! Yes, I want to see Jee!” Penny cheers.
Maddie leads Jee out to the yard, and then there is a flurry of hellos and hugs and comments on the status of Buck and Eddie’s relationship. At the very least, Ravi is there. Ravi doesn’t know Buck. Eddie gets to introduce them with no jokes. So that’s a singular win.
He gets two more significant ones, in the forms of solo conversations with Bobby, first, and then Maddie.
He finds himself alone with Bobby in the kitchen about a half an hour after he arrives, grabbing a round of drink refills for people. Bobby is working away on dinner.
“So,” he says, when Eddie walks into the room. Eddie knows that tone. He should have expected this.
“So?” Eddie replies. Though he can almost predict what Bobby will say next.
“You seem really happy,” Bobby observes.
Eddie smiles. “I am. Actually, I'm happier than I’ve really been, if I’m being honest. Only problem is that it’s not in LA.”
“I’m really glad to hear that, Eddie,” he says. “I was surprised when I heard, but… But it makes sense. A lot of sense, actually.”
Eddie’s not sure he knows what Bobby means by that, but he appreciates it nonetheless.
“Can I ask you something?”
Bobby nods. “Shoot.”
“Why didn’t you tell me the two of you made up?” Eddie asks.
Bobby smiles ruefully. “I’d wondered if that would bother you.”
“It doesn’t bother me,” Eddie replies, a little more bothered sounding than he intends. “Just, I thought we were both mad, and that we never talked about it, because you were hurt.”
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36 for🪷
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“He believed you?” Eddie asks. “Just like that?”
Buck shrugs. “I mean I’m not sure he doesn’t think I’m experiencing psychosis, but regardless, it was enough to get him in the car.”
“This is going to keep happening,” Bobby sighs. “No one is going to believe it. They’re all going to be upset. We might as well just FaceTime them.”
“We could,” Eddie says. “But there’s an AI for that these days. People just chat with the computer version of their dead loved ones, burning up the earth’s remaining water supply instead of going to therapy.”
Bobby winces.
“You’re so judgy,” Buck says, nudging him.
“It’s a point of principle,” Eddie replies. “What would Chris say?”
“Chris would be just as judgy, because you raised him that way,” Buck smirks.
“How is Chris?” Bobby asks.
“Good,” Eddie smiles. “He’s good. Almost twenty-five, as hard as that is to say out loud.”
“Wow,” Bobby whistles.
“Lives nearby,” Eddie says. “His roommate is the 114’s newest probie.”
Buck blushes. “You told him?”
“Of course I told him,” Eddie replies.
“Which probie?” Bobby asks. “And, by the way, very proud of you, Buck. Always knew that’s where you’d end up.”
Buck’s blush deepens.
“Thank you,” he mumbles. “Means a lot.”
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Because 🔭 is done, 36 for
again!
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“Denny Wilson,” Eddie adds. “That’s Buck’s new probie. Isn’t that wild?”
Bobby blinks, surprised. “Buck, are you just collecting everyone’s kids?”
Buck shrugs. “Chris calls our station Next Gen NYC and I have no idea what it means.”
“Well, neither do I,” Bobby says. “How’s Denny doing?”
“Great,” Buck smiles. “He’s got a great head on his shoulders.”
Bobby feels dizzy. Chris, an engineer. Harry and Denny, firefighters. They were just kids. Even Harry, seventeen, that’s still a kid. And when he met them all? They were so tiny.
“You okay?” Buck asks gently.
Bobby nods. “Just a lot to catch up on.”
“You have time,” Eddie assures him. “If… If you want us to lay off telling you things, it’s okay. You have time.”
Bobby nods. “Yeah. Maybe for now I just focus on Harry, and then on getting word to Athena.”
“We can do that,” Eddie agrees. “One step at a time.”
One step at a time, sure. Bobby still just doesn’t know which direction he’s headed in.
Eddie
Eddie and Buck watch through the window as Harry arrives. Bobby sort of springs to his feet when he hears the car pull into the driveway. He meets Harry on their front stoop. To Harry’s credit, he handles it better than Eddie.
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AI’s energy use already represents as much as 20 percent of global data-center power demand, research published Thursday in the journal Joule shows. That demand from AI, the research states, could double by the end of this year, comprising nearly half of all total data-center electricity consumption worldwide, excluding the electricity used for bitcoin mining.
The new research is published in a commentary by Alex de Vries-Gao, the founder of Digiconomist, a research company that evaluates the environmental impact of technology. De Vries-Gao started Digiconomist in the late 2010s to explore the impact of bitcoin mining, another extremely energy-intensive activity, would have on the environment. Looking at AI, he says, has grown more urgent over the past few years because of the widespread adoption of ChatGPT and other large language models that use massive amounts of energy. According to his research, worldwide AI energy demand is now set to surpass demand from bitcoin mining by the end of this year.
“The money that bitcoin miners had to get to where they are today is peanuts compared to the money that Google and Microsoft and all these big tech companies are pouring in [to AI],” he says. “This is just escalating a lot faster, and it’s a much bigger threat.”
The development of AI is already having an impact on Big Tech’s climate goals. Tech giants have acknowledged in recent sustainability reports that AI is largely responsible for driving up their energy use. Google’s greenhouse gas emissions, for instance, have increased 48 percent since 2019, complicating the company’s goals of reaching net zero by 2030.
“As we further integrate AI into our products, reducing emissions may be challenging due to increasing energy demands from the greater intensity of AI compute,” Google’s 2024 sustainability report reads.
Last month, the International Energy Agency released a report finding that data centers made up 1.5 percent of global energy use in 2024—around 415 terrawatt-hours, a little less than the yearly energy demand of Saudi Arabia. This number is only set to get bigger: Data centers’ electricity consumption has grown four times faster than overall consumption in recent years, while the amount of investment in data centers has nearly doubled since 2022, driven largely by massive expansions to account for new AI capacity. Overall, the IEA predicted that data center electricity consumption will grow to more than 900 TWh by the end of the decade.
But there’s still a lot of unknowns about the share that AI, specifically, takes up in that current configuration of electricity use by data centers. Data centers power a variety of services—like hosting cloud services and providing online infrastructure—that aren’t necessarily linked to the energy-intensive activities of AI. Tech companies, meanwhile, largely keep the energy expenditure of their software and hardware private.
Some attempts to quantify AI’s energy consumption have started from the user side: calculating the amount of electricity that goes into a single ChatGPT search, for instance. De Vries-Gao decided to look, instead, at the supply chain, starting from the production side to get a more global picture.
The high computing demands of AI, De Vries-Gao says, creates a natural “bottleneck” in the current global supply chain around AI hardware, particularly around the Taiwan Semiconductor Manufacturing Company (TSMC), the undisputed leader in producing key hardware that can handle these needs. Companies like Nvidia outsource the production of their chips to TSMC, which also produces chips for other companies like Google and AMD. (Both TSMC and Nvidia declined to comment for this article.)
De Vries-Gao used analyst estimates, earnings call transcripts, and device details to put together an approximate estimate of TSMC’s production capacity. He then looked at publicly available electricity consumption profiles of AI hardware and estimates on utilization rates of that hardware—which can vary based on what it’s being used for—to arrive at a rough figure of just how much of global data-center demand is taken up by AI. De Vries-Gao calculates that without increased production, AI will consume up to 82 terrawatt-hours of electricity this year—roughly around the same as the annual electricity consumption of a country like Switzerland. If production capacity for AI hardware doubles this year, as analysts have projected it will, demand could increase at a similar rate, representing almost half of all data center demand by the end of the year.
Despite the amount of publicly available information used in the paper, a lot of what De Vries-Gao is doing is peering into a black box: We simply don’t know certain factors that affect AI’s energy consumption, like the utilization rates of every piece of AI hardware in the world or what machine learning activities they’re being used for, let alone how the industry might develop in the future.
Sasha Luccioni, an AI and energy researcher and the climate lead at open-source machine-learning platform Hugging Face, cautioned about leaning too hard on some of the conclusions of the new paper, given the amount of unknowns at play. Luccioni, who was not involved in this research, says that when it comes to truly calculating AI’s energy use, disclosure from tech giants is crucial.
“It’s because we don’t have the information that [researchers] have to do this,” she says. “That’s why the error bar is so huge.”
And tech companies do keep this information. In 2022, Google published a paper on machine learning and electricity use, noting that machine learning was “10%–15% of Google’s total energy use” from 2019 to 2021, and predicted that with best practices, “by 2030 total carbon emissions from training will reduce.” However, since that paper—which was released before Google Gemini’s debut in 2023—Google has not provided any more detailed information about how much electricity ML uses. (Google declined to comment for this story.)
“You really have to deep-dive into the semiconductor supply chain to be able to make any sensible statement about the energy demand of AI,” De Vries-Gao says. “If these big tech companies were just publishing the same information that Google was publishing three years ago, we would have a pretty good indicator” of AI’s energy use.
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Economy Predictions: Part 1 (Post-Trump)
. . • ☆ . ° .• °:. *₊ ° . ☆
Prices will go up by at least 1.5% (accounting for inflation)
Social security collapse or severe downgrade
Trump tries tariffs, they backfire, and he backtracks
Hoover 2.0
We have the equivalent of a second Great Depression Reincarnated
Gas prices temporarily go down, while grocery and other cost-of-living prices skyrocket
Investments in AI companies will perform well, and investments in small businesses will perform more poorly
Some notable companies that haven’t shifted enough online for misc goods will collapse or go bankrupt
It will be much more difficult to be successful as a small business
More pressure on domestic factories causes an increase in demand for Hispanic workers, except ICE depleted available workers
The U.S dollar tanks in value and brings down other currencies dependent on it
The job market is garbage so American citizens and graduates emigrate for work
Massive hit to the agriculture industry as a result of immigration laws
Initially strict regulation becomes more lax again
They never address the temporary food shortage caused by lack of immigrant workers
#donald trump#trump#fuck trump#us politics#usa#politics#united states#election 2024#2028 elections#this was wild to theorize#made a few days ago right before he was inaguarated#so a few r already happening
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Hello there!
Welcome to my little corner of the internet.
Here we talk about the writing process, worldbuilding, tropes, character design, and being an author. Also queerness and asexuality specifically, with the occasional bit of shower thoughts, AI-bashing, and a few mini essays here and there on whatever I'm feeling like.
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Interested in some vampire fantasy? How 'bout some merfolk?


Eternal Night of the Northern Sky
Three hundred years ago, the vampire covens of the North took the sun from the sky. In the frozen wasteland that remains, clans of the living cling to warmth in a way the vampires never predicted—hunting the undead down for the fire in their veins. When Clan Maewag’s last blood slave takes their own life, Elias joins the hunting party in braving the surface. When the worst happens, Elias finds himself trusting a vampire to save him from the Freeze. Conflict brews between a coven thriving in a glittering utopia of equality and a coven enduring on blood slave servitude, with Elias trapped in the middle. What makes a monster in the sunless, frozen North, where survival demands Elias betray home, his people, and every truth he’s ever known?
Genres: New Adult, Queet Lit, Dark Fantasy
Available in ebook and paperback!
4.1.25: Interested in a free signed copy? Head to my author website and fill out the short form for yours, while supplies last.
—
Tell Me How Long
Finley McCann is an aspiring marine biologist, spending her days watching the ocean she loves die before her feet as the world spins on unmoved to stop it. Three years after a chance meeting with a survivor of a species thought extinct for centuries, Finley stumbles on an opportunity to save a Mer, and shock the world into acting before it’s too late. Tell Me How Long is a twist on the modern merfolk myth, and what it takes to survive under the threat of humanity in the open ocean.
Genres: Contemporary Sci-Fi, Mystery
Available in ebook!
Some notable posts of mine:
How to make your writing less stiff (1-9)
Dialogue Tags (Ohhhhh)
Character Dynamics the world needs more of
10 more of those
5 more of those
Yet another 5 of those
Aaaand 3 more
My stance on generative AI
On Foreshadowing
On Pacing
On Fantasy Worldbuilding
And that thereabouts covers some of the big ones? As always requests are open!
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Based on the search results, here are some innovative technologies that RideBoom could implement to enhance the user experience and stay ahead of ONDC:
Enhanced Safety Measures: RideBoom has already implemented additional safety measures, including enhanced driver background checks, real-time trip monitoring, and improved emergency response protocols. [1] To stay ahead, they could further enhance safety by integrating advanced telematics and AI-powered driver monitoring systems to ensure safe driving behavior.
Personalized and Customizable Services: RideBoom could introduce a more personalized user experience by leveraging data analytics and machine learning to understand individual preferences and offer tailored services. This could include features like customizable ride preferences, personalized recommendations, and the ability to save preferred routes or driver profiles. [1]
Seamless Multimodal Integration: To provide a more comprehensive transportation solution, RideBoom could integrate with other modes of transportation, such as public transit, bike-sharing, or micro-mobility options. This would allow users to plan and book their entire journey seamlessly through the RideBoom app, enhancing the overall user experience. [1]
Sustainable and Eco-friendly Initiatives: RideBoom has already started introducing electric and hybrid vehicles to its fleet, but they could further expand their green initiatives. This could include offering incentives for eco-friendly ride choices, partnering with renewable energy providers, and implementing carbon offset programs to reduce the environmental impact of their operations. [1]
Innovative Payment and Loyalty Solutions: To stay competitive with ONDC's zero-commission model, RideBoom could explore innovative payment options, such as integrated digital wallets, subscription-based services, or loyalty programs that offer rewards and discounts to frequent users. This could help attract and retain customers by providing more value-added services. [2]
Robust Data Analytics and Predictive Capabilities: RideBoom could leverage advanced data analytics and predictive modeling to optimize their operations, anticipate demand patterns, and proactively address user needs. This could include features like dynamic pricing, intelligent routing, and personalized recommendations to enhance the overall user experience. [1]
By implementing these innovative technologies, RideBoom can differentiate itself from ONDC, provide a more seamless and personalized user experience, and stay ahead of the competition in the on-demand transportation market.
#rideboom#rideboom app#delhi rideboom#ola cabs#biketaxi#uber#rideboom taxi app#ola#uber driver#uber taxi#rideboomindia#rideboom uber
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Ok since episode 5 is tomorrow, we need to review what happened in the previous episodes and what happened in the trailer so we can predict what is going to happen in episode five
In episode 1 ,"The Elastic Banana of Consciousness"
Pomni, a confused elbow disguised as a jester hat, logs into a corrupted educational math game from 1997 and immediately loses her sense of brunch. She meets a bunch of equally glitched individuals: a literal talking exclamation mark named Jax, a depressed marshmallow named Ragatha, and a cube of sentient soap called Caine, who insists he’s both the ringmaster and your dad.
Caine introduces Pomni to the Digital Circus, which is not a circus, nor digital, but rather a highly compressed pocket of psychological soup filled with balloon animals that whisper Latin. Every character seems chill until someone mentions “the exit,” at which point the walls bleed confetti and a vending machine starts screaming.
Midway through, Pomni is chased by a hallway that’s allergic to logic and ends up in the Void, a non-place that contains every browser tab you’ve ever left open. There, she meets a creature made entirely of obsolete TikTok dances who tries to explain free will using interpretive jazz.
Meanwhile, Jax hides beans in people’s shoes “just in case,” Ragatha attempts to build a friendship pyramid using wet spaghetti, and Kinger—the chess-obsessed metaphor for your uncle's trauma—tries to marry a lamp.
Eventually, everything loops like a cursed screensaver, and Pomni realizes she can’t log out because the logout button is actually a disguised metaphor for fear of abandonment. The episode ends with Caine flossing uncontrollably and screaming, “Welcome to the circus! We have emotional damage!”
In episode 2 ,
“Glitch of the Gooey Gargoyle”
Pomni wakes up to find that her legs have been replaced with tiny pogo sticks that won't stop bouncing unless she speaks exclusively in limericks. Meanwhile, Jax decides he's going to start a "gargoyle breeding program" after mistaking a corrupted JPEG file for a magical egg.
Ragatha becomes convinced that she's a muffin and demands to be toasted in the digital sun, while Kinger insists he has uncovered a secret code in the pixelated wallpaper that will lead them all to the “Gummy Realm of Eternal Slight Discomfort.”
Chaos escalates when Caine hosts a mandatory "Trust Fall Tournament" inside a virtual dimension made entirely of banana pudding. Participants must trust fall into their worst fears while being serenaded by AI-generated country music sung backward.
Gangle accidentally summons the Gooey Gargoyle, a sticky, glitchy beast with the head of a rubber duck and the body of wet candy corn. It speaks only in outdated internet memes and leaks emotional data from everyone it touches.
To defeat it, the gang must:
Perform a synchronized dance using only their elbows
Solve a riddle shouted by a holographic toaster
Sacrifice something “deeply metaphorical, but also slightly crunchy”
In the end, Pomni manages to reset her legs by rhyming “existential dread” with “pixelated bread,” and the Gooey Gargoyle melts into a puddle that Jax tries to bottle and sell as “Glitch Sauce.”
Caine claps, declares it all “part of the experience,” and teleports everyone into a giant rubber chicken for next week's challenge.End Scene: The camera zooms in on a tiny fly trapped in a jar labeled "Plot Coherence – DO NOT OPEN."
Then in episode 3,
“The Toenail of Truth”
The episode begins with Zooble waking up inside a giant bowl of alphabet soup that only spells out passive-aggressive messages. They quickly discover that someone has replaced all doors in the circus with sentient, judgmental salad bars that demand a detailed emotional monologue before opening.
Meanwhile, Caine announces that this week’s “lesson” is about “truth, trust, and toenails.” He reveals that one of the cast members has been hiding a secret... and the only way to discover the truth is by finding the ancient artifact: The Toenail of Truth, a glowing, 8-foot-long toenail said to grant absolute honesty to whoever sniffs it.
Subplots include:
Kinger believes the Toenail is haunting him and starts wearing 12 hats to “block the honesty waves.”
Gangle attempts to sculpt her feelings but accidentally brings her sculpture to life, and it immediately joins a punk band.
Pomni is convinced that the toenail contains the exit code to leave the digital world, so she teams up with a philosophical vending machine named Carl who only dispenses cryptic haikus and mayonnaise packets.
As the crew explores a maze made of unused CAPTCHA tests and infinite loading screens, they encounter hostile pop-up ads, a chorus of sock puppets reenacting their traumas, and a talking stapler who insists he's their new dad.
Eventually, Jax finds the Toenail lodged inside a floating disco pineapple guarded by 37 clones of himself, each more sarcastic than the last. After a chaotic battle of wit, juggling, and interpretive dance, they bring the Toenail back...
...only to discover that the “truth” it reveals is just everyone’s browser history, projected on the walls in neon Comic Sans.
Climax: Everyone runs screaming as their most embarrassing thoughts are revealed, but Pomni saves the day by smearing digital peanut butter on the Toenail, which causes it to crash and reboot into a regular piece of toast.
Final Scene: The group sits silently as the toast gives them vague life advice in a Morgan Freeman-esque voice while slowly spinning in midair.
Caine laughs maniacally and says, “Now wasn’t that enlightening?” before vanishing into a cereal box labeled “FREE SADNESS INSIDE.”
And finally, in episode 4,
“The Quest for the Spaghetti Moon”
Plot Summary:
The episode kicks off with Pomni accidentally triggering the "Spaghetti Moon" prophecy while trying to reboot the circus' Wi-Fi. According to an ancient, glitchy scroll she finds inside a vending machine, the Spaghetti Moon is a celestial event where spaghetti rains from the sky, and whoever catches the most noodles gets their deepest, weirdest wish granted… but only if they make it through a series of absurd trials.
The gang is thrust into a wild race to the Spaghetti Moon, but the rules are ever-changing, and nobody really understands anything. Caine announces that they will have to "earn the noodles" through a series of mini-games involving both brainpower and spaghetti-fueled athleticism.
Mini-Games Include:
Noodle Jousting: Contestants ride on flying meatballs and joust with noodle lances made out of rubber bands and existential dread.
Spaghetti Knowledge Quiz: A game show hosted by a sentient jar of marinara sauce that only asks questions about obscure 90s cartoons and internet forum history.
Spaghetti Time Travel: Jax accidentally rewinds time by 5 minutes every time he blinks, but only when it’s absolutely inconvenient.
Carbonara Yoga: A rigorous yoga session where the floor is made of lasagna, and every pose must be held while chanting “Al Dente” in unison.
Amidst all the chaos, Ragatha discovers that the Spaghetti Moon is an ancient digital virus that threatens to “delete” reality itself if they don’t reach it first. But instead of panicking, she turns the impending catastrophe into a fashion trend, creating a new line of spaghetti-themed hats for everyone.
Subplot: Gangle, after a deep conversation with a spaghetti cloud that asks her if she’s ever felt “truly al dente,” begins to question her purpose in life. She contemplates becoming a pasta philosopher. Her deep thoughts are only interrupted by Kinger, who insists that the Spaghetti Moon holds the secret to “Quantum Tacos”, and they need to travel through a giant glowing fork to find the “Meatball Multiverse.”
After endless noodle-related obstacles and a bizarre encounter with Spaghetto, a mafia boss made entirely of pasta and meatballs who speaks in cryptic rhymes, the crew finally arrives at the Spaghetti Moon, which, to their horror, turns out to be... an oversized ravioli.
As they try to harvest their wish-granting noodles, Caine reveals the twist: only the person who can cook the perfect pasta will be granted a wish. The group ends up in a giant digital kitchen, with each contestant racing to cook a dish while battling against an army of sentient spaghetti forks.
Climax: Pomni wins by accidentally cooking a perfect “spaghetti paradox” that is both overcooked and undercooked at the same time, causing the moon to implode into a giant spaghetti tornado. Instead of granting wishes, it sends the gang into a “lasagna dimension”, where everyone is stuck in an eternal loop of layering pasta and sauce.Ending Scene: Caine gives a dramatic monologue about “the nature of pasta” and “the futility of wishes” while the group slowly dissolves into a puddle of marinara sauce and Parmesan dust. In the final shot, the Spaghetti Moon flickers out of existence, replaced by a floating jar of pickles that whispers “Next time, just read the manual.”
Now let's review what happened in the trailer and make predictions for the fifth episode,
“Pinball Paradox”
Trailer Breakdown:
The trailer starts with Jax gleefully being ejected out of a giant pinball machine, his arms flailing like rubber noodles, with the words “WELCOME TO THE FLIP SIDE” flashing in neon lights above him. His eyes are wide with excitement, but also slightly glitching.
Suddenly, the circus tent shudders, and a loud voice (possibly Caine, possibly a malfunctioning Roomba) says, “The Flippers are HERE!” Cue a fast montage of everyone being sucked into a bizarre pinball world made of bouncing trampolines, glowing pachinko machines, and sentient bowling balls. The gang is screaming in both joy and fear.
Predictions:
The Pinball Machine Dimension: Everyone is transported into a giant, sentient pinball machine where the flippers are actually evil sentient ping-pong paddles that refuse to let anyone get past them without first answering a riddle about cereal mascots. They also might randomly shoot out rubber chickens instead of balls, causing chaos.
Pomni’s "Flipping Identity Crisis": Pomni spends half the episode trapped in a loop where every time she lands, she forgets who she is, only to remember the second she gets flung again. She meets her "flipped" self, who is now a disco ball and claims to be the “Real Pomni”. They have a heated debate about identity and what it means to be a digital construct, all while bouncing between various pinball bumpers.
Gangle's New Career: Gangle starts a pinball-themed improv comedy troupe in the middle of the chaos, recruiting a neon-clad pachinko ball named Marty. They perform extremely avant-garde performances about the meaning of digital existence, which are met with confused applause from the rest of the crew.
Ragatha’s “Pinball Wizard” Moment: Ragatha gets an epiphany and begins to channel her inner Pinball Wizard, thinking that if she can play the game perfectly, it will grant her an escape. She becomes one with the machine, wearing a glowing helmet that looks suspiciously like a toaster. By the end, she is teleported to a digital version of Earth, but it’s all just pancakes, and she has to figure out how to exist in this pancake reality. She also has to dodge syrup floods while solving complex breakfast metaphors.
Kinger's "Time Travel Pinball" Theory: Kinger believes that the pinball machine is a time loop device. The more you flip, the more you age in digital years. As a result, he starts talking to himself in the future tense and predicts that in 2 hours, he will have already solved the “mystery” of the episode by riding a giant marshmallow to the moon.
The Flippers' Origin Story: The evil Flippers reveal their backstory in a completely unexpected, musical number. Apparently, they were once just regular flip-flops left on a beach by a digital vacation simulator. After being exposed to "too much feedback," they gained sentience and became obsessed with high-speed, unpredictable motion. Their goal? To flip the circus into an alternate dimension where everything is upside down and off-center, just like them.
Caine’s Final Reveal: In the end, Caine dramatically announces that the only way to escape the Pinball Dimension is to score the highest points on the digital scoreboard. The twist? He’s secretly been cheating the entire time by manipulating the scoreboard with his “super secret Caine powers,” and nobody cares, because the game makes zero sense anyway.
Cliffhanger Ending:
As the episode closes, the camera zooms out to show the entire circus now stuck inside the pinball machine, each member floating in midair like helpless digital marbles. Pomni is being chased by a glowing, angry paddle, while Ragatha laughs maniacally in the corner, surrounded by pancakes. Jax is still trying to figure out what the “exit flipper” does, but no one’s really sure if the exit even exists.The final shot is a giant ball of confetti that gets sucked into the machine, followed by the text: “TO BE CONTINUED… MAYBE?”
#the amazing digital circus#tadc jax#tadc pomni#tadc ragatha#tadc#tadc kinger#tadc gangle#tadc zooble#tadc caine#glitch productions#I totally didn't use chatgpt for this#WHY ARE THE TAGS BREAKING UP!?#tadc episode 5
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Crystallography-informed AI achieves high performance in predicting novel crystal structures
A research team from the Institute of Statistical Mathematics and Panasonic Holdings Corporation has developed a machine learning algorithm, ShotgunCSP, that enables fast and accurate prediction of crystal structures from material compositions. The algorithm achieved world-leading performance in crystal structure prediction benchmarks. Crystal structure prediction seeks to identify the stable or metastable crystal structures for any given chemical compound adopted under specific conditions. Traditionally, this process relies on iterative energy evaluations using time-consuming first-principles calculations and solving energy minimization problems to find stable atomic configurations. This challenge has been a cornerstone of materials science since the early 20th century. Recently, advancements in computational technology and generative AI have enabled new approaches in this field. However, for large-scale or complex molecular systems, the exhaustive exploration of vast phase spaces demands enormous computational resources, making it an unresolved issue in materials science.
Read more.
#Materials Science#Science#Crystals#Machine learning#Computational materials science#Crystal structure
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Excerpt from this story from Heated:
Energy experts warned only a few years ago that the world had to stop building new fossil fuel projects to preserve a livable climate.
Now, artificial intelligence is driving a rapid expansion of methane gas infrastructure—pipelines and power plants—that experts say could have devastating climate consequences if fully realized.
As large language models like ChatGPT become more sophisticated, experts predict that the nation’s energy demands will grow by a “shocking” 16 percent in the next five years. Tech giants like Amazon, Meta, and Alphabet have increasingly turned to nuclear power plants or large renewable energy projects to power data centers that use as much energy as a small town.
But those cleaner energy sources will not be enough to meet the voracious energy demands of AI, analysts say. To bridge the gap, tech giants and fossil fuel companies are planning to build new gas power plants and pipelines that directly supply data centers. And they increasingly propose keeping those projects separate from the grid, fast tracking gas infrastructure at a speed that can’t be matched by renewables or nuclear.
The growth of AI has been called the “savior” of the gas industry. In Virginia alone, the data center capital of the world, a new state report found that AI demand could add a new 1.5 gigawatt gas plant every two years for 15 consecutive years.
And now, as energy demand for AI rises, oil corporations are planning to build gas plants that specifically serve data centers. Last week, Exxon announced that it is building a large gas plant that will directly supply power to data centers within the next five years. The company claims the gas plant will use technology that captures polluting emissions—despite the fact that the technology has never been used at a commercial scale before.
Chevron also announced that the company is preparing to sell gas to an undisclosed number of data centers. “We're doing some work right now with a number of different people that's not quite ready for prime time, looking at possible solutions to build large-scale power generation,” said CEO Mike Wirth at an Atlantic Council event. The opportunity to sell power to data centers is so promising that even private equity firms are investing billions in building energy infrastructure.
But the companies that will benefit the most from an AI gas boom, according to S&P Global, are pipeline companies. This year, several major U.S. pipeline companies told investors that they were already in talks to connect their sprawling pipeline networks directly to on-site gas power plants at data centers.
“We, frankly, are kind of overwhelmed with the number of requests that we’re dealing with, ” Williams CEO Alan Armstrong said on a call with analysts. The pipeline company, which owns the 10,000 mile Transco system, is expanding its existing pipeline network from Virginia to Alabama partly to “provide reliable power where data center growth is expected,” according to Williams.
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