#Remote Training Software

[leveluplms]

Discover top-tier Remote Training LMS software in Calgary, designed to streamline employee learning and development. Our platform offers flexible, cloud-based solutions tailored for remote teams, ensuring seamless training anytime, anywhere. Empower your workforce with engaging content, progress tracking, and real-time analytics—all in one user-friendly learning management system.

[whatimdoing-here]

When I started my current position, basically all of my immediate coworkers were in the US. Probably over 20 or 30 of us. We added one in Europe to cover that time zone.

Then we got bought out a few years ago and slowly... Now there are me and 2 others in the US (near me), 1 in Canada. 1 in England, the rest in India.

One of the not fun things about that is logging on at 730 am and having a full inbox, and people who still can't figure out how to their job asking to talk on the phone.

[jobyoda-philippines]

Exploring Career and Job Opportunities in Davao City Philippines

Davao City, recognized as one of the Philippines' most progressive cities, continues to experience remarkable economic growth, creating a vibrant job market that attracts professionals from across the country. The city's diverse economy offers numerous employment opportunities, from entry-level positions to executive roles, making it an attractive destination for job seekers at all career stages.

The Business Process Outsourcing (BPO) sector stands as one of the largest employers in Davao City, providing thousands of jobs across various specializations. Companies in this sector actively recruit customer service representatives, technical support specialists, and quality assurance analysts, offering competitive salaries and comprehensive benefits packages. The industry's continued expansion has created numerous opportunities for career advancement, with many organizations promoting from within and providing extensive training programs.

Part-time employment opportunities have also flourished in Davao City, catering to students, professionals seeking additional income, and individuals preferring flexible work arrangements. The retail sector, food service industry, and education field offer numerous part-time positions with varying schedules and responsibilities. These roles often provide valuable work experience and can serve as stepping stones to full-time careers.

The Information Technology sector in Davao has seen significant growth, with many companies seeking software developers, web designers, and IT support specialists. This growth has been fueled by the city's improving technological infrastructure and the increasing number of tech-focused businesses establishing operations in the region. Tech professionals can find opportunities in both established companies and startups, with many positions offering competitive compensation and the possibility of remote work arrangements.

Davao's hospitality and tourism industry continues to expand, creating jobs in hotels, restaurants, travel agencies, and tour operations. The sector offers positions ranging from entry-level service roles to management positions, with many employers providing training and development opportunities. The industry's growth has also sparked demand for professionals in events management and tourism marketing.

The education sector presents numerous opportunities for both full-time and part-time employment. Educational institutions regularly seek teachers, tutors, and administrative staff. The rise of online learning has created additional opportunities for English language teachers and academic consultants who can work flexible hours from home or teaching centers.

Job hiring  in Davao, the digital economy has opened new avenues for employment. E-commerce specialists, digital content creators, and social media managers are in high demand as businesses increasingly establish their online presence. These positions often offer the flexibility of remote work while providing competitive compensation packages.

Professional development resources are readily available in Davao City, with numerous institutions offering skills training programs and industry certifications. Job seekers can access career counseling services, resume writing assistance, and interview coaching through various employment support organizations. These resources prove invaluable in helping candidates prepare for and secure desired positions.

The financial services sector in Davao has also experienced substantial growth, creating opportunities for banking professionals, insurance specialists, and investment consultants. These positions typically offer attractive compensation packages, including performance bonuses and health benefits, making them highly sought after by experienced professionals.

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For those entering Davao's job market, proper preparation is essential. Successful job seekers typically maintain updated resumes, prepare comprehensive portfolios, and stay informed about industry developments. Professional networking, both online and offline, plays a crucial role in discovering opportunities and advancing careers in the city.

The future of Davao's job market looks promising, with emerging industries creating new employment opportunities. The city's commitment to economic development, coupled with its strategic location and robust infrastructure, continues to attract businesses and investors, ensuring a steady stream of job opportunities for qualified candidates.

Whether seeking full-time employment or part-time job in Davao City offers a diverse range of opportunities across multiple industries. Success in this dynamic job market often comes to those who combine proper preparation with continuous skill development and effective networking. As the city continues to grow and evolve, its job market remains a beacon of opportunity for professionals seeking to build meaningful careers in Mindanao's premier business hub.

[teophan]

someone reblogged a post from me saying “if you’ve ever used spellcheck you’ve used AI” so that dumbass is blocked now

[vidyalayalms]

Remote Training Software | LMS for Remote Training

Train Anywhere, Grow Everywhere – Empower Your Workforce Remotely!

Exercise your employees anywhere with our end-to-end external training software-a strong external learning platform which is an engineer to provide simple, interactive and scalable training experience. Whether you need to place new higher or upskill current teams on the ship, our Remote Training LMS Software provides distance training AI-I-controlled personal learning, confusing virtual classes and provides adaptable assessment tools that keep your employees motivated and exhausting. Instructors can easily create and maintain materials, and real -time monitoring of progress, as well as powerful analysis provides rich insights on employee development. With our solution, you can use consistent high-quality training in places and develop a future capable workforce scaling with your business-what time and anywhere.

Read More

[cassandraturcotte]

Master Skills with Virtual Training

This infographic highlights the transformative benefits of virtual training in mastering new skills.

[jaysonmurphyitservice]

Jayson Murphy IT service

Website: http://jaysonmurphyitservicer.com/

Address: 609 New York Ave, Brooklyn, NY 11203, USA

Phone: 917-577-3337

Jayson Murphy IT Service is a comprehensive provider of managed IT solutions tailored to meet the unique needs of businesses. With a focus on enhancing operational efficiency and ensuring robust cybersecurity, we offer a range of services including network management, cloud solutions, data backup, and IT consulting. Our team of experienced professionals is dedicated to delivering reliable support and innovative technology strategies that empower organizations to thrive in a digital landscape. At Jayson Murphy IT Service, we prioritize customer satisfaction and work closely with our clients to develop customized solutions that drive growth and success.

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[eatossolutions]

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[callcenterwfhsoftware]

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[uqualio]

uQualio is an innovative Employee Training platform revolutionizing how companies educate their workforce. With user-friendly interface and customizable content, uQualio offers a seamless learning experience. Its interactive features engage employees, ensuring better retention. From onboarding to skill enhancement, uQualio caters to diverse training needs. Track progress effortlessly with analytics. With uQualio, empower your team with knowledge anytime, anywhere.

[nostalgebraist]

Anthropic's stated "AI timelines" seem wildly aggressive to me.

As far as I can tell, they are now saying that by 2028 – and possibly even by 2027, or late 2026 – something they call "powerful AI" will exist.

And by "powerful AI," they mean... this (source, emphasis mine):

In terms of pure intelligence, it is smarter than a Nobel Prize winner across most relevant fields – biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc. In addition to just being a “smart thing you talk to”, it has all the “interfaces” available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. It can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world. It does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary. It does not have a physical embodiment (other than living on a computer screen), but it can control existing physical tools, robots, or laboratory equipment through a computer; in theory it could even design robots or equipment for itself to use. The resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed. It may however be limited by the response time of the physical world or of software it interacts with. Each of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks.

In the post I'm quoting, Amodei is coy about the timeline for this stuff, saying only that

I think it could come as early as 2026, though there are also ways it could take much longer. But for the purposes of this essay, I’d like to put these issues aside [...]

However, other official communications from Anthropic have been more specific. Most notable is their recent OSTP submission, which states (emphasis in original):

Based on current research trajectories, we anticipate that powerful AI systems could emerge as soon as late 2026 or 2027 [...] Powerful AI technology will be built during this Administration. [i.e. the current Trump administration -nost]

See also here, where Jack Clark says (my emphasis):

People underrate how significant and fast-moving AI progress is. We have this notion that in late 2026, or early 2027, powerful AI systems will be built that will have intellectual capabilities that match or exceed Nobel Prize winners. They’ll have the ability to navigate all of the interfaces… [Clark goes on, mentioning some of the other tenets of "powerful AI" as in other Anthropic communications -nost]

----

To be clear, extremely short timelines like these are not unique to Anthropic.

Miles Brundage (ex-OpenAI) says something similar, albeit less specific, in this post. And Daniel Kokotajlo (also ex-OpenAI) has held views like this for a long time now.

Even Sam Altman himself has said similar things (though in much, much vaguer terms, both on the content of the deliverable and the timeline).

Still, Anthropic's statements are unique in being

official positions of the company

extremely specific and ambitious about the details

extremely aggressive about the timing, even by the standards of "short timelines" AI prognosticators in the same social cluster

Re: ambition, note that the definition of "powerful AI" seems almost the opposite of what you'd come up with if you were trying to make a confident forecast of something.

Often people will talk about "AI capable of transforming the world economy" or something more like that, leaving room for the AI in question to do that in one of several ways, or to do so while still failing at some important things.

But instead, Anthropic's definition is a big conjunctive list of "it'll be able to do this and that and this other thing and...", and each individual capability is defined in the most aggressive possible way, too! Not just "good enough at science to be extremely useful for scientists," but "smarter than a Nobel Prize winner," across "most relevant fields" (whatever that means). And not just good at science but also able to "write extremely good novels" (note that we have a long way to go on that front, and I get the feeling that people at AI labs don't appreciate the extent of the gap [cf]). Not only can it use a computer interface, it can use every computer interface; not only can it use them competently, but it can do so better than the best humans in the world. And all of that is in the first two paragraphs – there's four more paragraphs I haven't even touched in this little summary!

Re: timing, they have even shorter timelines than Kokotajlo these days, which is remarkable since he's historically been considered "the guy with the really short timelines." (See here where Kokotajlo states a median prediction of 2028 for "AGI," by which he means something less impressive than "powerful AI"; he expects something close to the "powerful AI" vision ["ASI"] ~1 year or so after "AGI" arrives.)

----

I, uh, really do not think this is going to happen in "late 2026 or 2027."

Or even by the end of this presidential administration, for that matter.

I can imagine it happening within my lifetime – which is wild and scary and marvelous. But in 1.5 years?!

The confusing thing is, I am very familiar with the kinds of arguments that "short timelines" people make, and I still find the Anthropic's timelines hard to fathom.

Above, I mentioned that Anthropic has shorter timelines than Daniel Kokotajlo, who "merely" expects the same sort of thing in 2029 or so. This probably seems like hairsplitting – from the perspective of your average person not in these circles, both of these predictions look basically identical, "absurdly good godlike sci-fi AI coming absurdly soon." What difference does an extra year or two make, right?

But it's salient to me, because I've been reading Kokotajlo for years now, and I feel like I basically get understand his case. And people, including me, tend to push back on him in the "no, that's too soon" direction. I've read many many blog posts and discussions over the years about this sort of thing, I feel like I should have a handle on what the short-timelines case is.

But even if you accept all the arguments evinced over the years by Daniel "Short Timelines" Kokotajlo, even if you grant all the premises he assumes and some people don't – that still doesn't get you all the way to the Anthropic timeline!

To give a very brief, very inadequate summary, the standard "short timelines argument" right now is like:

Over the next few years we will see a "growth spurt" in the amount of computing power ("compute") used for the largest LLM training runs. This factor of production has been largely stagnant since GPT-4 in 2023, for various reasons, but new clusters are getting built and the metaphorical car will get moving again soon. (See here)

By convention, each "GPT number" uses ~100x as much training compute as the last one. GPT-3 used ~100x as much as GPT-2, and GPT-4 used ~100x as much as GPT-3 (i.e. ~10,000x as much as GPT-2).

We are just now starting to see "~10x GPT-4 compute" models (like Grok 3 and GPT-4.5). In the next few years we will get to "~100x GPT-4 compute" models, and by 2030 will will reach ~10,000x GPT-4 compute.

If you think intuitively about "how much GPT-4 improved upon GPT-3 (100x less) or GPT-2 (10,000x less)," you can maybe convince yourself that these near-future models will be super-smart in ways that are difficult to precisely state/imagine from our vantage point. (GPT-4 was way smarter than GPT-2; it's hard to know what "projecting that forward" would mean, concretely, but it sure does sound like something pretty special)

Meanwhile, all kinds of (arguably) complementary research is going on, like allowing models to "think" for longer amounts of time, giving them GUI interfaces, etc.

All that being said, there's still a big intuitive gap between "ChatGPT, but it's much smarter under the hood" and anything like "powerful AI." But...

...the LLMs are getting good enough that they can write pretty good code, and they're getting better over time. And depending on how you interpret the evidence, you may be able to convince yourself that they're also swiftly getting better at other tasks involved in AI development, like "research engineering." So maybe you don't need to get all the way yourself, you just need to build an AI that's a good enough AI developer that it improves your AIs faster than you can, and then those AIs are even better developers, etc. etc. (People in this social cluster are really keen on the importance of exponential growth, which is generally a good trait to have but IMO it shades into "we need to kick off exponential growth and it'll somehow do the rest because it's all-powerful" in this case.)

And like, I have various disagreements with this picture.

For one thing, the "10x" models we're getting now don't seem especially impressive – there has been a lot of debate over this of course, but reportedly these models were disappointing to their own developers, who expected scaling to work wonders (using the kind of intuitive reasoning mentioned above) and got less than they hoped for.

And (in light of that) I think it's double-counting to talk about the wonders of scaling and then talk about reasoning, computer GUI use, etc. as complementary accelerating factors – those things are just table stakes at this point, the models are already maxing out the tasks you had defined previously, you've gotta give them something new to do or else they'll just sit there wasting GPUs when a smaller model would have sufficed.

And I think we're already at a point where nuances of UX and "character writing" and so forth are more of a limiting factor than intelligence. It's not a lack of "intelligence" that gives us superficially dazzling but vapid "eyeball kick" prose, or voice assistants that are deeply uncomfortable to actually talk to, or (I claim) "AI agents" that get stuck in loops and confuse themselves, or any of that.

We are still stuck in the "Helpful, Harmless, Honest Assistant" chatbot paradigm – no one has seriously broke with it since that Anthropic introduced it in a paper in 2021 – and now that paradigm is showing its limits. ("Reasoning" was strapped onto this paradigm in a simple and fairly awkward way, the new "reasoning" models are still chatbots like this, no one is actually doing anything else.) And instead of "okay, let's invent something better," the plan seems to be "let's just scale up these assistant chatbots and try to get them to self-improve, and they'll figure it out." I won't try to explain why in this post (IYI I kind of tried to here) but I really doubt these helpful/harmless guys can bootstrap their way into winning all the Nobel Prizes.

----

All that stuff I just said – that's where I differ from the usual "short timelines" people, from Kokotajlo and co.

But OK, let's say that for the sake of argument, I'm wrong and they're right. It still seems like a pretty tough squeeze to get to "powerful AI" on time, doesn't it?

In the OSTP submission, Anthropic presents their latest release as evidence of their authority to speak on the topic:

In February 2025, we released Claude 3.7 Sonnet, which is by many performance benchmarks the most powerful and capable commercially-available AI system in the world.

I've used Claude 3.7 Sonnet quite a bit. It is indeed really good, by the standards of these sorts of things!

But it is, of course, very very far from "powerful AI." So like, what is the fine-grained timeline even supposed to look like? When do the many, many milestones get crossed? If they're going to have "powerful AI" in early 2027, where exactly are they in mid-2026? At end-of-year 2025?

If I assume that absolutely everything goes splendidly well with no unexpected obstacles – and remember, we are talking about automating all human intellectual labor and all tasks done by humans on computers, but sure, whatever – then maybe we get the really impressive next-gen models later this year or early next year... and maybe they're suddenly good at all the stuff that has been tough for LLMs thus far (the "10x" models already released show little sign of this but sure, whatever)... and then we finally get into the self-improvement loop in earnest, and then... what?

They figure out to squeeze even more performance out of the GPUs? They think of really smart experiments to run on the cluster? Where are they going to get all the missing information about how to do every single job on earth, the tacit knowledge, the stuff that's not in any web scrape anywhere but locked up in human minds and inaccessible private data stores? Is an experiment designed by a helpful-chatbot AI going to finally crack the problem of giving chatbots the taste to "write extremely good novels," when that taste is precisely what "helpful-chatbot AIs" lack?

I guess the boring answer is that this is all just hype – tech CEO acts like tech CEO, news at 11. (But I don't feel like that can be the full story here, somehow.)

And the scary answer is that there's some secret Anthropic private info that makes this all more plausible. (But I doubt that too – cf. Brundage's claim that there are no more secrets like that now, the short-timelines cards are all on the table.)

It just does not make sense to me. And (as you can probably tell) I find it very frustrating that these guys are out there talking about how human thought will basically be obsolete in a few years, and pontificating about how to find new sources of meaning in life and stuff, without actually laying out an argument that their vision – which would be the common concern of all of us, if it were indeed on the horizon – is actually likely to occur on the timescale they propose.

It would be less frustrating if I were being asked to simply take it on faith, or explicitly on the basis of corporate secret knowledge. But no, the claim is not that, it's something more like "now, now, I know this must sound far-fetched to the layman, but if you really understand 'scaling laws' and 'exponential growth,' and you appreciate the way that pretraining will be scaled up soon, then it's simply obvious that –"

No! Fuck that! I've read the papers you're talking about, I know all the arguments you're handwaving-in-the-direction-of! It still doesn't add up!

[sabertoothwalrus]

hi!! do you have any advice on how to finish projects faster? or at least more efficiently? i take a few days to finish a piece (1 or 2 days at minimum) and i want to learn how to refine my process

that can depend a lot on what kind of look you’re trying to achieve, and what exactly is slowing you down!

things you can do if you take too long doing lineart:

Practice sketching in pen & marker! Do exercises that train your hand to be more efficient. If you can draw the same thing with 5 lines that previously took you 20, you’ll cut down on time.

Try a different brush! Maybe the one you’re using is too soft, and you have to keep going back over the lines to make them dark enough. There might be another brush that gets the same result with less effort.

Zoom out! On paper, a drawing that’s 2 inches tall will take wayyyy less time than a drawing that’s as big as your torso. When you zoom in, you’re essentially making the whole drawing bigger. When I draw, I like to be able to see the whole pose. If you’re worried about it not being perfectly clean, I promise you, no one is paying that close attention.

Skip the lineart entirely! Odds are, your sketches might already be pretty clean. If it takes you 20 minutes to do a sketch and 2 hours to do the lineart, but the lines look almost the same, then why bother doing the lineart?

similar advice for coloring/rendering!

Maybe it’s your art software! I can color 10x faster in CSP than anything else, because CSP makes it really easy to color in flats.

Limit how many types of brushes you use. There ARE certain effects (like convincing digital watercolor) that really do need 5-10 different brushes to get the look Just Right, but going through your tool menus to swap brushes will add time. When I render (which is rare, honestly) I stick to one, maybe two painterly brushes.

other general advice:

Don’t be so hard on yourself! Honestly, 1-2 days is still objectively pretty fast!

If you’re a perfectionist who will arbitrarily spend too much time fiddling and fiddling until it’s justttttt right, try setting timers! Give yourself a predetermined amount of time for the lineart, for the coloring, for the rendering, etc and MOVE ON once that timer goes off. Not everything you do has to be your magnum opus.

Use keyboard shortcuts!!!!!!!! I don’t like using screen tablets, especially if I can’t use shortcuts. If you have a tablet with programmable buttons or some kind of remote, that can work too. I see people use bluetooth xbox controllers sometimes, which is a good option if you already have that. Personally, I use so many shortcuts that there are never enough buttons to program, so I just stick with a keyboard.

JUST KEEP AT IT! The more you draw, the faster you get. I avoided doing paneled comics for nearly 10 years cause they took so much effort, and would only do comics where each panel was its own layer/image. After enough time doing that, I eventually got good enough at everything else to do with comics that the paneling aspect wasn’t that difficult anymore.

[mostlysignssomeportents]

Conspiratorialism as a material phenomenon

I'll be in TUCSON, AZ from November 8-10: I'm the GUEST OF HONOR at the TUSCON SCIENCE FICTION CONVENTION.

I think it behooves us to be a little skeptical of stories about AI driving people to believe wrong things and commit ugly actions. Not that I like the AI slop that is filling up our social media, but when we look at the ways that AI is harming us, slop is pretty low on the list.

The real AI harms come from the actual things that AI companies sell AI to do. There's the AI gun-detector gadgets that the credulous Mayor Eric Adams put in NYC subways, which led to 2,749 invasive searches and turned up zero guns:

https://www.cbsnews.com/newyork/news/nycs-subway-weapons-detector-pilot-program-ends/

Any time AI is used to predict crime – predictive policing, bail determinations, Child Protective Services red flags – they magnify the biases already present in these systems, and, even worse, they give this bias the veneer of scientific neutrality. This process is called "empiricism-washing," and you know you're experiencing it when you hear some variation on "it's just math, math can't be racist":

https://pluralistic.net/2020/06/23/cryptocidal-maniacs/#phrenology

When AI is used to replace customer service representatives, it systematically defrauds customers, while providing an "accountability sink" that allows the company to disclaim responsibility for the thefts:

https://pluralistic.net/2024/04/23/maximal-plausibility/#reverse-centaurs

When AI is used to perform high-velocity "decision support" that is supposed to inform a "human in the loop," it quickly overwhelms its human overseer, who takes on the role of "moral crumple zone," pressing the "OK" button as fast as they can. This is bad enough when the sacrificial victim is a human overseeing, say, proctoring software that accuses remote students of cheating on their tests:

https://pluralistic.net/2022/02/16/unauthorized-paper/#cheating-anticheat

But it's potentially lethal when the AI is a transcription engine that doctors have to use to feed notes to a data-hungry electronic health record system that is optimized to commit health insurance fraud by seeking out pretenses to "upcode" a patient's treatment. Those AIs are prone to inventing things the doctor never said, inserting them into the record that the doctor is supposed to review, but remember, the only reason the AI is there at all is that the doctor is being asked to do so much paperwork that they don't have time to treat their patients:

https://apnews.com/article/ai-artificial-intelligence-health-business-90020cdf5fa16c79ca2e5b6c4c9bbb14

My point is that "worrying about AI" is a zero-sum game. When we train our fire on the stuff that isn't important to the AI stock swindlers' business-plans (like creating AI slop), we should remember that the AI companies could halt all of that activity and not lose a dime in revenue. By contrast, when we focus on AI applications that do the most direct harm – policing, health, security, customer service – we also focus on the AI applications that make the most money and drive the most investment.

AI hasn't attracted hundreds of billions in investment capital because investors love AI slop. All the money pouring into the system – from investors, from customers, from easily gulled big-city mayors – is chasing things that AI is objectively very bad at and those things also cause much more harm than AI slop. If you want to be a good AI critic, you should devote the majority of your focus to these applications. Sure, they're not as visually arresting, but discrediting them is financially arresting, and that's what really matters.

All that said: AI slop is real, there is a lot of it, and just because it doesn't warrant priority over the stuff AI companies actually sell, it still has cultural significance and is worth considering.

AI slop has turned Facebook into an anaerobic lagoon of botshit, just the laziest, grossest engagement bait, much of it the product of rise-and-grind spammers who avidly consume get rich quick "courses" and then churn out a torrent of "shrimp Jesus" and fake chainsaw sculptures:

https://www.404media.co/email/1cdf7620-2e2f-4450-9cd9-e041f4f0c27f/

For poor engagement farmers in the global south chasing the fractional pennies that Facebook shells out for successful clickbait, the actual content of the slop is beside the point. These spammers aren't necessarily tuned into the psyche of the wealthy-world Facebook users who represent Meta's top monetization subjects. They're just trying everything and doubling down on anything that moves the needle, A/B splitting their way into weird, hyper-optimized, grotesque crap:

https://www.404media.co/facebook-is-being-overrun-with-stolen-ai-generated-images-that-people-think-are-real/

In other words, Facebook's AI spammers are laying out a banquet of arbitrary possibilities, like the letters on a Ouija board, and the Facebook users' clicks and engagement are a collective ideomotor response, moving the algorithm's planchette to the options that tug hardest at our collective delights (or, more often, disgusts).

So, rather than thinking of AI spammers as creating the ideological and aesthetic trends that drive millions of confused Facebook users into condemning, praising, and arguing about surreal botshit, it's more true to say that spammers are discovering these trends within their subjects' collective yearnings and terrors, and then refining them by exploring endlessly ramified variations in search of unsuspected niches.

(If you know anything about AI, this may remind you of something: a Generative Adversarial Network, in which one bot creates variations on a theme, and another bot ranks how closely the variations approach some ideal. In this case, the spammers are the generators and the Facebook users they evince reactions from are the discriminators)

https://en.wikipedia.org/wiki/Generative_adversarial_network

I got to thinking about this today while reading User Mag, Taylor Lorenz's superb newsletter, and her reporting on a new AI slop trend, "My neighbor’s ridiculous reason for egging my car":

https://www.usermag.co/p/my-neighbors-ridiculous-reason-for

The "egging my car" slop consists of endless variations on a story in which the poster (generally a figure of sympathy, canonically a single mother of newborn twins) complains that her awful neighbor threw dozens of eggs at her car to punish her for parking in a way that blocked his elaborate Hallowe'en display. The text is accompanied by an AI-generated image showing a modest family car that has been absolutely plastered with broken eggs, dozens upon dozens of them.

According to Lorenz, variations on this slop are topping very large Facebook discussion forums totalling millions of users, like "Movie Character…,USA Story, Volleyball Women, Top Trends, Love Style, and God Bless." These posts link to SEO sites laden with programmatic advertising.

The funnel goes:

i. Create outrage and hence broad reach;

ii, A small percentage of those who see the post will click through to the SEO site;

iii. A small fraction of those users will click a low-quality ad;

iv. The ad will pay homeopathic sub-pennies to the spammer.

The revenue per user on this kind of scam is next to nothing, so it only works if it can get very broad reach, which is why the spam is so designed for engagement maximization. The more discussion a post generates, the more users Facebook recommends it to.

These are very effective engagement bait. Almost all AI slop gets some free engagement in the form of arguments between users who don't know they're commenting an AI scam and people hectoring them for falling for the scam. This is like the free square in the middle of a bingo card.

Beyond that, there's multivalent outrage: some users are furious about food wastage; others about the poor, victimized "mother" (some users are furious about both). Not only do users get to voice their fury at both of these imaginary sins, they can also argue with one another about whether, say, food wastage even matters when compared to the petty-minded aggression of the "perpetrator." These discussions also offer lots of opportunity for violent fantasies about the bad guy getting a comeuppance, offers to travel to the imaginary AI-generated suburb to dole out a beating, etc. All in all, the spammers behind this tedious fiction have really figured out how to rope in all kinds of users' attention.

Of course, the spammers don't get much from this. There isn't such a thing as an "attention economy." You can't use attention as a unit of account, a medium of exchange or a store of value. Attention – like everything else that you can't build an economy upon, such as cryptocurrency – must be converted to money before it has economic significance. Hence that tooth-achingly trite high-tech neologism, "monetization."

The monetization of attention is very poor, but AI is heavily subsidized or even free (for now), so the largest venture capital and private equity funds in the world are spending billions in public pension money and rich peoples' savings into CO2 plumes, GPUs, and botshit so that a bunch of hustle-culture weirdos in the Pacific Rim can make a few dollars by tricking people into clicking through engagement bait slop – twice.

The slop isn't the point of this, but the slop does have the useful function of making the collective ideomotor response visible and thus providing a peek into our hopes and fears. What does the "egging my car" slop say about the things that we're thinking about?

Lorenz cites Jamie Cohen, a media scholar at CUNY Queens, who points out that subtext of this slop is "fear and distrust in people about their neighbors." Cohen predicts that "the next trend, is going to be stranger and more violent.”

This feels right to me. The corollary of mistrusting your neighbors, of course, is trusting only yourself and your family. Or, as Margaret Thatcher liked to say, "There is no such thing as society. There are individual men and women and there are families."

We are living in the tail end of a 40 year experiment in structuring our world as though "there is no such thing as society." We've gutted our welfare net, shut down or privatized public services, all but abolished solidaristic institutions like unions.

This isn't mere aesthetics: an atomized society is far more hospitable to extreme wealth inequality than one in which we are all in it together. When your power comes from being a "wise consumer" who "votes with your wallet," then all you can do about the climate emergency is buy a different kind of car – you can't build the public transit system that will make cars obsolete.

When you "vote with your wallet" all you can do about animal cruelty and habitat loss is eat less meat. When you "vote with your wallet" all you can do about high drug prices is "shop around for a bargain." When you vote with your wallet, all you can do when your bank forecloses on your home is "choose your next lender more carefully."

Most importantly, when you vote with your wallet, you cast a ballot in an election that the people with the thickest wallets always win. No wonder those people have spent so long teaching us that we can't trust our neighbors, that there is no such thing as society, that we can't have nice things. That there is no alternative.

The commercial surveillance industry really wants you to believe that they're good at convincing people of things, because that's a good way to sell advertising. But claims of mind-control are pretty goddamned improbable – everyone who ever claimed to have managed the trick was lying, from Rasputin to MK-ULTRA:

https://pluralistic.net/HowToDestroySurveillanceCapitalism

Rather than seeing these platforms as convincing people of things, we should understand them as discovering and reinforcing the ideology that people have been driven to by material conditions. Platforms like Facebook show us to one another, let us form groups that can imperfectly fill in for the solidarity we're desperate for after 40 years of "no such thing as society."

The most interesting thing about "egging my car" slop is that it reveals that so many of us are convinced of two contradictory things: first, that everyone else is a monster who will turn on you for the pettiest of reasons; and second, that we're all the kind of people who would stick up for the victims of those monsters.

Tor Books as just published two new, free LITTLE BROTHER stories: VIGILANT, about creepy surveillance in distance education; and SPILL, about oil pipelines and indigenous landback.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/10/29/hobbesian-slop/#cui-bono

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[elodieunderglass]

this feels like a strange question but in light of your info about how jockeys don't usually know or train with the horses they race on - what are jockeys..... for? what is the jockey doing that the horse couldn't be trained to do independently? does a good or bad jockey make a significant difference to how well a given horse does in a race?

Right?!

In a way, asking what the jockey’s for also asks the question of “why race horses?” Why do it at all, and why horses?

We sort of do it because horses are fast and exciting, and because they do what we tell them, even though it’s not in their nature. Because it’s not their nature, they have a jockey.

I’ve put this under a “Keep Reading” to save your dash.

Horses could be trained to race by themselves to some extent, but it wouldn’t be like greyhound racing - greyhounds are sighthounds, running perfectly reasonable dog software on top of ancient and serviceable dog hardware, practicing a variation of hunting behaviour. Horses wouldn’t do this; they have little desire to chase a mechanical rabbit. they have even less plan than a greyhound about what they’d do if they caught it. (Also, in terms of animal welfare, greyhound racing isn’t widely celebrated; loose animals running around aren’t better off than controlled ones.)

Racing-to-find-a-winner is not herding behaviour, even though some horses do seem to possess a natural interest in the topic. You could train some of them to understand better, and that’s what racehorse training is, but the way we have of training that is to put someone on their back to explain to them what their job is, so it all becomes circular anyway. Why do it? Why not? Why do humans race horses? Why race horses? We could just race snails; it’d be cheaper!

One answer is that when horses just Go, it isn’t super Fun. They mostly Go to pieces.

The jockey is the pilot, or software, who understands the situation and has a goal to achieve. The horse is not an engine, but a thinking animal; they have their own goals and interests, which are often satisfied by just running around in a predator-confusing fashion with their friends for 2 minutes, and then crashing into a car, eating hot chips and lying. Most of them do not really care how long 3 minutes is, what a mile means, what “pacing” is, or what “winning” is. They just have Go, and so they do that for a bit, and then fuck off.

I guess another metaphor would be Mario Kart. There are various combinations of automated and human players in a game of Mario Kart, and if racing was just about going fast, the fastest vehicle should always win. But a decent human player can beat the NPCs even if the human hasn’t bothered min/maxxing a vehicle, just because they can be moderately smart about how to race. An adult can often beat a child at Mario Kart, even if the adult takes a much worse vehicle, because in theory, brains/experience/strategy/planning factor into “who wins a race,” and we LIKE that.

Same with car racing. Why not just race autonomous vehicles? In F1, where they build their own cars, why not include the driving software in the design? Or why not remote-control them? Why bother strapping a poor driver into a flameproof suit? Fans will tell you it’s strategy. The human driver uses tactics and responsiveness and skill - but, below all this, the dark red thread of the human is risking their life and we like that.

In theory, jockeys are more intelligent than thoroughbreds, and have more of a plan: setting pace, knowing what time is, changing strategy, evaluating stamina, conducting the horse safely through traffic and over jumps, and adding a complicating element of human interest. In practice, it’s believed that they have relatively little influence on race outcomes - a bad jockey on a good horse can win or lose a race; a good jockey on a bad horse usually just loses; oh, what the hell, let’s just race snails instead - but without the jockeys, you’d have to change the name of the sport to Horses Wandering Around A Carpark Kicking Lumps Off Each Other.

Here is a bunch of baby steeplechasers practicing the concept of Go in such a way that nobody gets to Go at all. After the un-mounted Snow Dragon wipes out most of the other horses and jockeys, all of the loose horses go faster without the weight of their riders, but after an initial show of interest in the concept, the loose horses all lose interest and focus.

It was funny (because nobody was hurt) but it wasn’t what anyone really wanted. In theory, that’s what the jockey is for: they’re supposed to be the adult, in a game where you can win by doing that.

But none of it has to be happening, any more than Investments need to be Managed, you know? It would also be fine if we didn’t! Michael O’Sullivan, an Irish jockey, just died racing this very week and there’s the dark red thread again: the human is risking their life.

The consumption of animal and human in an ancient sport is fascinating and visceral and compelling; but you’re right to question it; none of it has to be that way.

As for the second half of your question: a bad jockey can make a good horse lose. A good jockey cannot make a bad horse win. But most people and most horses are not particularly exceptional, or particularly anything at all; they are just workers running in a circle.

Top jockeys on average horses win more often than other people on average horses. Top jockeys and champions exist, with year-on-year records and recorded material evidence of their decision-making and risks paying off, indicating that there’s consistency of winning across skill and experience that makes their success better-than/random; it would be worth doing a study controlling for the fact that top people are offered the best mounts.

It’s a test of horsemanship, too. Achieving flow - nonverbal command of an animal and fellow athlete, and sympathy together, such that they respect and trust you - having just met the animal - is an achievement of many skills, and if you broke a jockey’s skills down into different types, most ordinary people couldn’t do any of them. No core strength, no balance, bad hands, bad posture, no sense of body positioning, no internal timer, no ability to psychically mind-meld with an unhinged animal you don’t know personally… they’re all fairly rare, and it’s something else to make it complex and interesting for people who like that sort of thing.

Personally, I just like Killie’s little problems and the drama around them. The racing industry itself could collapse tomorrow, rendering Killie’s story historical fiction, and I’d be just as happy.

[sexymemecoin]

The Metaverse: A New Frontier in Digital Interaction

The concept of the metaverse has captivated the imagination of technologists, futurists, and businesses alike. Envisioned as a collective virtual shared space, the metaverse merges physical and digital realities, offering immersive experiences and unprecedented opportunities for interaction, commerce, and creativity. This article delves into the metaverse, its potential impact on various sectors, the technologies driving its development, and notable projects shaping this emerging landscape.

What is the Metaverse?

The metaverse is a digital universe that encompasses virtual and augmented reality, providing a persistent, shared, and interactive online environment. In the metaverse, users can create avatars, interact with others, attend virtual events, own virtual property, and engage in economic activities. Unlike traditional online experiences, the metaverse aims to replicate and enhance the real world, offering seamless integration of the physical and digital realms.

Key Components of the Metaverse

Virtual Worlds: Virtual worlds are digital environments where users can explore, interact, and create. Platforms like Decentraland, Sandbox, and VRChat offer expansive virtual spaces where users can build, socialize, and participate in various activities.

Augmented Reality (AR): AR overlays digital information onto the real world, enhancing user experiences through devices like smartphones and AR glasses. Examples include Pokémon GO and AR navigation apps that blend digital content with physical surroundings.

Virtual Reality (VR): VR provides immersive experiences through headsets that transport users to fully digital environments. Companies like Oculus, HTC Vive, and Sony PlayStation VR are leading the way in developing advanced VR hardware and software.

Blockchain Technology: Blockchain plays a crucial role in the metaverse by enabling decentralized ownership, digital scarcity, and secure transactions. NFTs (Non-Fungible Tokens) and cryptocurrencies are integral to the metaverse economy, allowing users to buy, sell, and trade virtual assets.

Digital Economy: The metaverse features a robust digital economy where users can earn, spend, and invest in virtual goods and services. Virtual real estate, digital art, and in-game items are examples of assets that hold real-world value within the metaverse.

Potential Impact of the Metaverse

Social Interaction: The metaverse offers new ways for people to connect and interact, transcending geographical boundaries. Virtual events, social spaces, and collaborative environments provide opportunities for meaningful engagement and community building.

Entertainment and Gaming: The entertainment and gaming industries are poised to benefit significantly from the metaverse. Immersive games, virtual concerts, and interactive storytelling experiences offer new dimensions of engagement and creativity.

Education and Training: The metaverse has the potential to revolutionize education and training by providing immersive, interactive learning environments. Virtual classrooms, simulations, and collaborative projects can enhance educational outcomes and accessibility.

Commerce and Retail: Virtual shopping experiences and digital marketplaces enable businesses to reach global audiences in innovative ways. Brands can create virtual storefronts, offer unique digital products, and engage customers through immersive experiences.

Work and Collaboration: The metaverse can transform the future of work by providing virtual offices, meeting spaces, and collaborative tools. Remote work and global collaboration become more seamless and engaging in a fully digital environment.

Technologies Driving the Metaverse

5G Connectivity: High-speed, low-latency 5G networks are essential for delivering seamless and responsive metaverse experiences. Enhanced connectivity enables real-time interactions and high-quality streaming of immersive content.

Advanced Graphics and Computing: Powerful graphics processing units (GPUs) and cloud computing resources are crucial for rendering detailed virtual environments and supporting large-scale metaverse platforms.

Artificial Intelligence (AI): AI enhances the metaverse by enabling realistic avatars, intelligent virtual assistants, and dynamic content generation. AI-driven algorithms can personalize experiences and optimize virtual interactions.

Wearable Technology: Wearable devices, such as VR headsets, AR glasses, and haptic feedback suits, provide users with immersive and interactive experiences. Advancements in wearable technology are critical for enhancing the metaverse experience.

Notable Metaverse Projects

Decentraland: Decentraland is a decentralized virtual world where users can buy, sell, and develop virtual real estate as NFTs. The platform offers a wide range of experiences, from gaming and socializing to virtual commerce and education.

Sandbox: Sandbox is a virtual world that allows users to create, own, and monetize their gaming experiences using blockchain technology. The platform's user-generated content and virtual real estate model have attracted a vibrant community of creators and players.

Facebook's Meta: Facebook's rebranding to Meta underscores its commitment to building the metaverse. Meta aims to create interconnected virtual spaces for social interaction, work, and entertainment, leveraging its existing social media infrastructure.

Roblox: Roblox is an online platform that enables users to create and play games developed by other users. With its extensive user-generated content and virtual economy, Roblox exemplifies the potential of the metaverse in gaming and social interaction.

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The Future of the Metaverse

The metaverse is still in its early stages, but its potential to reshape digital interaction is immense. As technology advances and more industries explore its possibilities, the metaverse is likely to become an integral part of our daily lives. Collaboration between technology providers, content creators, and businesses will drive the development of the metaverse, creating new opportunities for innovation and growth.

Conclusion

The metaverse represents a new frontier in digital interaction, offering immersive and interconnected experiences that bridge the physical and digital worlds. With its potential to transform social interaction, entertainment, education, commerce, and work, the metaverse is poised to revolutionize various aspects of our lives. Notable projects like Decentraland, Sandbox, Meta, Roblox, and Sexy Meme Coin are at the forefront of this transformation, showcasing the diverse possibilities within this emerging digital universe.

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