#What is the Future of AI-Powered Development in Business?

[intelisync]

The Future of Business Growth: AI-Powered Development Strat

AI-powered development is revolutionizing business growth, efficiency, and innovation. By 2024, businesses that harness AI's potential will achieve unprecedented growth, outpacing their competitors. AI's incorporation into business operations enhances productivity, accuracy, and customer experience, driving revenue growth. McKinsey's report indicates that AI could deliver an additional $13 trillion to the global economy by 2030. With the global AI market expected to grow at a CAGR of 37.3% from 2023 to 2030, AI's role in business is becoming increasingly crucial.

AI-powered development uses advanced technologies like machine learning, natural language processing, and computer vision to perform tasks that typically require human intelligence. AI is transforming industries from finance to healthcare, providing solutions like automated trading systems and predictive diagnostics. AI enhances efficiency by automating repetitive tasks, optimizing operations, and enabling employees to focus on strategic activities. AI-driven chatbots and virtual assistants offer real-time support and personalized interactions, improving customer experience. AI's predictive analytics capabilities provide data-driven insights, helping businesses make informed decisions and stay ahead of market trends.

For businesses to fully leverage AI's benefits, a strategic approach to AI implementation is essential. This includes evaluating goals, identifying data sources, selecting appropriate AI tools, and investing in training and education. Addressing challenges like data privacy, system integration, and ethical considerations is critical for successful AI adoption. Partnering with Intelisync can facilitate this process, providing comprehensive AI services that ensure successful AI integration and maximize business impact. Intelisync's expertise in machine learning, data analytics, and AI-driven automation helps businesses unlock their full potential. Contact Intelisync today to start your AI journey and transform your Learn more....

[probablyasocialecologist]

This is it. Generative AI, as a commercial tech phenomenon, has reached its apex. The hype is evaporating. The tech is too unreliable, too often. The vibes are terrible. The air is escaping from the bubble. To me, the question is more about whether the air will rush out all at once, sending the tech sector careening downward like a balloon that someone blew up, failed to tie off properly, and let go—or more slowly, shrinking down to size in gradual sputters, while emitting embarrassing fart sounds, like a balloon being deliberately pinched around the opening by a smirking teenager. But come on. The jig is up. The technology that was at this time last year being somberly touted as so powerful that it posed an existential threat to humanity is now worrying investors because it is apparently incapable of generating passable marketing emails reliably enough. We’ve had at least a year of companies shelling out for business-grade generative AI, and the results—painted as shinily as possible from a banking and investment sector that would love nothing more than a new technology that can automate office work and creative labor—are one big “meh.” As a Bloomberg story put it last week, “Big Tech Fails to Convince Wall Street That AI Is Paying Off.” From the piece: Amazon.com Inc., Microsoft Corp. and Alphabet Inc. had one job heading into this earnings season: show that the billions of dollars they’ve each sunk into the infrastructure propelling the artificial intelligence boom is translating into real sales. In the eyes of Wall Street, they disappointed. Shares in Google owner Alphabet have fallen 7.4% since it reported last week. Microsoft’s stock price has declined in the three days since the company’s own results. Shares of Amazon — the latest to drop its earnings on Thursday — plunged by the most since October 2022 on Friday. Silicon Valley hailed 2024 as the year that companies would begin to deploy generative AI, the type of technology that can create text, images and videos from simple prompts. This mass adoption is meant to finally bring about meaningful profits from the likes of Google’s Gemini and Microsoft’s Copilot. The fact that those returns have yet to meaningfully materialize is stoking broader concerns about how worthwhile AI will really prove to be. Meanwhile, Nvidia, the AI chipmaker that soared to an absurd $3 trillion valuation, is losing that value with every passing day—26% over the last month or so, and some analysts believe that’s just the beginning. These declines are the result of less-than-stellar early results from corporations who’ve embraced enterprise-tier generative AI, the distinct lack of killer commercial products 18 months into the AI boom, and scathing financial analyses from Goldman Sachs, Sequoia Capital, and Elliot Management, each of whom concluded that there was “too much spend, too little benefit” from generative AI, in the words of Goldman, and that it was “overhyped” and a “bubble” per Elliot. As CNN put it in its report on growing fears of an AI bubble, Some investors had even anticipated that this would be the quarter that tech giants would start to signal that they were backing off their AI infrastructure investments since “AI is not delivering the returns that they were expecting,” D.A. Davidson analyst Gil Luria told CNN. The opposite happened — Google, Microsoft and Meta all signaled that they plan to spend even more as they lay the groundwork for what they hope is an AI future. This can, perhaps, explain some of the investor revolt. The tech giants have responded to mounting concerns by doubling, even tripling down, and planning on spending tens of billions of dollars on researching, developing, and deploying generative AI for the foreseeable future. All this as high profile clients are canceling their contracts. As surveys show that overwhelming majorities of workers say generative AI makes them less productive. As MIT economist and automation scholar Daron Acemoglu warns, “Don’t believe the AI hype.”

6 August 2024

[covid-safer-hotties]

Also preserved in our archive (Updated daily!)

Researchers report that a new AI tool enhances the diagnostic process, potentially identifying more individuals who need care. Previous diagnostic studies estimated that 7 percent of the population suffers from long COVID. However, a new study using an AI tool developed by Mass General Brigham indicates a significantly higher rate of 22.8 percent.

The AI-based tool can sift through electronic health records to help clinicians identify cases of long COVID. The often-mysterious condition can encompass a litany of enduring symptoms, including fatigue, chronic cough, and brain fog after infection from SARS-CoV-2.

The algorithm used was developed by drawing de-identified patient data from the clinical records of nearly 300,000 patients across 14 hospitals and 20 community health centers in the Mass General Brigham system. The results, published in the journal Med, could identify more people who should be receiving care for this potentially debilitating condition.

“Our AI tool could turn a foggy diagnostic process into something sharp and focused, giving clinicians the power to make sense of a challenging condition,” said senior author Hossein Estiri, head of AI Research at the Center for AI and Biomedical Informatics of the Learning Healthcare System (CAIBILS) at MGB and an associate professor of medicine at Harvard Medical School. “With this work, we may finally be able to see long COVID for what it truly is — and more importantly, how to treat it.”

For the purposes of their study, Estiri and colleagues defined long COVID as a diagnosis of exclusion that is also infection-associated. That means the diagnosis could not be explained in the patient’s unique medical record but was associated with a COVID infection. In addition, the diagnosis needed to have persisted for two months or longer in a 12-month follow-up window.

Precision Phenotyping: A Novel Approach The novel method developed by Estiri and colleagues, called “precision phenotyping,” sifts through individual records to identify symptoms and conditions linked to COVID-19 to track symptoms over time in order to differentiate them from other illnesses. For example, the algorithm can detect if shortness of breath results from pre-existing conditions like heart failure or asthma rather than long COVID. Only when every other possibility was exhausted would the tool flag the patient as having long COVID.

“Physicians are often faced with having to wade through a tangled web of symptoms and medical histories, unsure of which threads to pull, while balancing busy caseloads. Having a tool powered by AI that can methodically do it for them could be a game-changer,” said Alaleh Azhir, co-lead author and an internal medicine resident at Brigham and Women’s Hospital, a founding member of the Mass General Brigham healthcare system.

The new tool’s patient-centered diagnoses may also help alleviate biases built into current diagnostics for long COVID, said researchers, who noted diagnoses with the official ICD-10 diagnostic code for long COVID trend toward those with easier access to healthcare.

The researchers said their tool is about 3 percent more accurate than the data ICD-10 codes capture, while being less biased. Specifically, their study demonstrated that the individuals they identified as having long COVID mirror the broader demographic makeup of Massachusetts, unlike long COVID algorithms that rely on a single diagnostic code or individual clinical encounters, skewing results toward certain populations such as those with more access to care.

“This broader scope ensures that marginalized communities, often sidelined in clinical studies, are no longer invisible,” said Estiri.

Limitations and Future Directions Limitations of the study and AI tool include the fact that health record data the algorithm uses to account for long COVID symptoms may be less complete than the data physicians capture in post-visit clinical notes. Another limitation was the algorithm did not capture the possible worsening of a prior condition that may have been a long COVID symptom. For example, if a patient had COPD that worsened before they developed COVID-19, the algorithm might have removed the episodes even if they were long COVID indicators. Declines in COVID-19 testing in recent years also makes it difficult to identify when a patient may have first gotten COVID-19.

The study was limited to patients in Massachusetts.

Future studies may explore the algorithm in cohorts of patients with specific conditions, like COPD or diabetes. The researchers also plan to release this algorithm publicly on open access so physicians and healthcare systems globally can use it in their patient populations.

In addition to opening the door to better clinical care, this work may lay the foundation for future research into the genetic and biochemical factors behind long COVID’s various subtypes. “Questions about the true burden of long COVID — questions that have thus far remained elusive — now seem more within reach,” said Estiri.

Reference: “Precision phenotyping for curating research cohorts of patients with unexplained post-acute sequelae of COVID-19” by Alaleh Azhir, Jonas Hügel, Jiazi Tian, Jingya Cheng, Ingrid V. Bassett, Douglas S. Bell, Elmer V. Bernstam, Maha R. Farhat, Darren W. Henderson, Emily S. Lau, Michele Morris, Yevgeniy R. Semenov, Virginia A. Triant, Shyam Visweswaran, Zachary H. Strasser, Jeffrey G. Klann, Shawn N. Murphy and Hossein Estiri, 8 November 2024, Med. DOI: 10.1016/j.medj.2024.10.009 www.cell.com/med/fulltext/S2666-6340(24)00407-0?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2666634024004070%3Fshowall%3Dtrue

[sanshofox]

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.

[diezmil10000]

when i was a teenager i used to spend too much time on social media. since i've always been into anime and otaku things, a lot of the japanese and south korean artists i looked up to were kind of distant; they didn't talk about their lives nor followed people back often. to my eyes, this was peak cool. these people drew so good that they didn't need to adapt to algorithms or foreign languages to succeed! i used to think that if i had so much power i wouldn't be able to resist the urge to use it to change the world.

at the same time, i also hated it. i hated when artists were so secretive about their process, so ungrateful towards the people who always supported them. i especially hated pick me artists who were constantly complaining about how hard it was to draw profiles and the other eye and who would mostly draw trends and memes and didn't understand the depth of the pieces of media they liked.

now i understand that my vision back then was blurred by a mix of admiration, bitterness and of course the language barrier. artists on social media are just random people. very few get to the point where someone else manages their account, or they start working for a studio, and even then it's still someone behind the screen.

i still have my takes about how certain types of online artists behave, but lately i've been trying to avoid those bad feelings and be more grateful for the fact that people are still creating, despite everything that's going on in the world. i'd rather be forced to follow a thousand amateur and/or attention-seeking artists than a shitty genAI account.

it's been about 8 years since i started posting my fanart online and i've met so many artists from completely different backgrounds. i've seen my friends grow and make art i would have never imagined they could make. i'm mutuals with people i've admired for almost a decade and i'm regularly told that my art inspires others. some manga authors and videogame developers have seen my art of their characters. it's been like this for years and i'm still not used to it. it's so nicel!! but it's still unbelievable.

i realized some time ago that i am now that type of unreachable artist to a lot of people. i feel guilty about it, but i don't know what to be sorry for. i guess that it was never about trying to be mysterious or forcing myself to hold back my opinions, it's just that the world is too big for one person to be on the spotlight. now that i have a job and i'm busy, i'm very comfortable in a spotlight i can turn off whenever i want.

(side note i still draw a lot but it's mostly my ocs and i'm embarrassed to post them)

if there's something i know for certain is that people will always want to see cool art. my family always asks for my drawings even if they're always girls making out and not the kind of paintings they wish i made. my friends who aren't artists still struggle to put into words why they like what i do, even if they don't know the characters; but the fact that they keep trying to communicate it makes me happy, because it shows that they really want me to continue doing this.

i don't need to hope that humanity keeps making art because i already know it will happen. but i wish people who are already on this path don't feel discouraged about the future, even with the rise of generative AI and fascism and the decline of social media platforms. the world is much more beautiful with everyone's creations in it and there's always room for more, we will always yearn for more.

i have no plans to stop making art unless i go blind, in which case i would probably learn to make music. i want to get better, i will get better, but i'm just a random person who happens to be alive at a time when random people post their art online. no matter where you are in your artistic journey, if you decide to keep moving forward, i'll meet you here in the spotlight.

[brain-rot-central]

If you ever wanted to know how bad the illiteracy crisis in America is, I work with people who are native English speakers, grew up going to public schools in areas that aren't necessarily poor or underfunded and they use AI grammar checkers in order to check how they speak/type on a daily basis.

Now, granted, they could have dyslexia.

I'm definitely some degree of dyslexic, but by exposing yourself to reading and listening to various different audio recordings, you start to develop a sense of "hmm this doesn't sound/look right;" almost like a type of pattern recognition.

I knew from a young age that I had difficulties with reading/writing/speaking. I STILL speak backwards and will often jumble the order of words in a sentence, to the point where I have to stop and restart. It's much easier for me to sound coherent through writing than speaking, and even then I sometimes struggle to get my point across.

My parents didn't want to admit I had a problem, so I took it upon myself to read/write as much as I could. I hated when it was my turn to read a passage from a book out loud during class, but I did my best to go over the passage as long as I could before being picked to read it, that way the words were already familiar in my mouth. If that makes sense.

What my point is though is that we neeeeeed to start encouraging people to read again. If you can't spend time reading because of kids or school or a busy schedule, by God pop on an audiobook and just listen. Not saying that all media should be free, but it really should be a lot easier for people to access books and other works. I think that would really help improve literacy rates nationwide.

I'd love to one day see local libraries have delivery services. Like order a book from your library online and they deliver it with a package slip to send it back through the mail after 2-3 weeks; however long they let you keep a book. If you want an extension maybe they make you pay an extra $1-5, something like that, which would cover the cost of packaging in most cases.

To see people using AI grammar checkers on the daily because they either did not have any help with reading/writing when they were younger or grew up impoverished breaks my heart and should not be the standard going forward.

Popping a sentence into a grammar checker will help you in the short-term, but if you want to get to a point where you never have to rely on such a device in the future, you need to practice that skill. And the only way you're going to do that is by putting the effort in to do so.

Not only does it benefit you by way of being able to convey yourself better, but it also helps keep your brain active. There have been multiple studies done that show people who read/play crosswords puzzles have a lower chance of developing memory loss as they age.

There really is truth in the statement, "you use it or you lose it."

I think this is something important to focus on because in a time where book bans are happening across the nation and there's widespread demonization of higher education, we have to realize that our ability to develop critical thinking skills is directly linked to how often we exercise our brains.

By keeping us illiterate, it becomes easier for oppressive governments to spoon feed us bullshit while no one bats an eye. I like to refer to the days of Medieval England and Europe when only those who had money and status were taught how to read. The Church basically ran everything and would very often spin the truth in their favor knowing the masses were illiterate and uneducated.

That's not something I would like to see in the year 2025, and I don't think most people want to see it, either.

Education is not the problem. Knowledge is truly power, and one of the best ways you can obtain knowledge is by reading.

Even if you struggle and you can't read something beyond Dr. Seuss, start there. Read as much at that level as you can, and slowly work yourself up. Keep challenging yourself.

If you need to write words down so you can look them up later, do it. Write them out in a book or a text note document on your phone with the definition next to them.

Do not let them strip your ability to gather information from you. Do not let them make you believe that to have knowledge or the desire to seek out knowledge is a bad thing.

Reading comprehension is one thing that can save you. You can read between the lines of whatever bullshit is being spun and thrown at you. Do not let them take that from you.

[mariacallous]

The damage the Trump administration has done to science in a few short months is both well documented and incalculable, but in recent days that assault has taken an alarming twist. Their latest project is not firing researchers or pulling funds—although there’s still plenty of that going on. It’s the inversion of science itself.

Here’s how it works. Three “dire wolves” are born in an undisclosed location in the continental United States, and the media goes wild. This is big news for Game of Thrones fans and anyone interested in “de-extinction,” the promise of bringing back long-vanished species.

There’s a lot to unpack here: Are these dire wolves really dire wolves? (They’re technically grey wolves with edited genes, so not everyone’s convinced.) Is this a publicity stunt or a watershed moment of discovery? If we’re staying in the Song of Ice and Fire universe, can we do ice dragons next?

All more or less reasonable reactions. And then there’s secretary of the interior Doug Burgum, a former software executive and investor now charged with managing public lands in the US. “The marvel of ‘de-extinction’ technology can help forge a future where populations are never at risk,” Burgum wrote in a post on X this week. “The revival of the Dire Wolf heralds the advent of a thrilling new era of scientific wonder, showcasing how the concept of ‘de-extinction’ can serve as a bedrock for modern species conservation.”

What Burgum is suggesting here is that the answer to 18,000 threatened species—as classified and tallied by the nonprofit International Union for Conservation of Nature—is that scientists can simply slice and dice their genes back together. It’s like playing Contra with the infinite lives code, but for the global ecosystem.

This logic is wrong, the argument is bad. More to the point, though, it’s the kind of upside-down takeaway that will be used not to advance conservation efforts but to repeal them. Oh, fracking may kill off the California condor? Here’s a mutant vulture as a make-good.

“Developing genetic technology cannot be viewed as the solution to human-caused extinction, especially not when this administration is seeking to actively destroy the habitats and legal protections imperiled species need,” said Mike Senatore, senior vice president of conservation programs at the nonprofit Defenders of Wildlife, in a statement. “What we are seeing is anti-wildlife, pro-business politicians vilify the Endangered Species Act and claim we can Frankenstein our way to the future.”

On Tuesday, Donald Trump put on a show of signing an executive order that promotes coal production in the United States. The EO explicitly cites the need to power data centers for artificial intelligence. Yes, AI is energy-intensive. They’ve got that right. Appropriate responses to that fact might include “can we make AI more energy-efficient?” or “Can we push AI companies to draw on renewable resources.” Instead, the Trump administration has decided that the linchpin technology of the future should be driven by the energy source of the past. You might as well push UPS to deliver exclusively by Clydesdale. Everything is twisted and nothing makes sense.

The nonsense jujitsu is absurd, but is it sincere? In some cases, it’s hard to say. In others it seems more likely that scientific illiteracy serves a cover for retribution. This week, the Commerce Department canceled federal support for three Princeton University initiatives focused on climate research. The stated reason, for one of those programs: “This cooperative agreement promotes exaggerated and implausible climate threats, contributing to a phenomenon known as ‘climate anxiety,’ which has increased significantly among America’s youth.”

Commerce Department, you’re so close! Climate anxiety among young people is definitely something to look out for. Telling them to close their eyes and stick their fingers in their ears while the world burns is probably not the best way to address it. If you think their climate stress is bad now, just wait until half of Miami is underwater.

There are two important pieces of broader context here. First is that Donald Trump does not believe in climate change, and therefore his administration proceeds as though it does not exist. Second is that Princeton University president Christopher Eisengruber had the audacity to suggest that the federal government not routinely shake down academic institutions under the guise of stopping antisemitism. Two weeks later, the Trump administration suspended dozens of research grants to Princeton totaling hundreds of millions of dollars. And now, “climate anxiety.”

This is all against the backdrop of a government whose leading health officials are Robert F. Kennedy Jr. and Mehmet Oz, two men who, to varying degrees, have built their careers peddling unscientific malarky. The Trump administration has made clear that it will not stop at the destruction and degradation of scientific research in the United States. It will also misrepresent, misinterpret, and bastardize it to achieve distinctly unscientific ends.

Those dire wolves aren’t going to solve anything; they’re not going to be reintroduced to the wild, they’re not going to help thin out deer and elk populations.

But buried in the announcement was something that could make a difference. It turns out Colossal also cloned a number of red wolves—a species that is critically endangered but very much not extinct—with the goal of increasing genetic diversity among the population. It doesn’t resurrect a species that humanity has wiped out. It helps one survive.

[togglesbloggle]

I won't be opting out of the AI scraping thing, though of course I'm glad they're giving us the option. In fact, at some point in the last year or so, I realized that 'the machine' is actually a part of why I'm writing in the first place, a conscious part of my audience.

All the old reasons are still there; this is a great place to practice writing, and I can feel proud looking back over the years and getting a sense of my own improvement at stringing words together, developing and communicating ideas. And I mean, social media is what it is. I'm not immune to the joy of getting a lot of notes on something that I worked hard on, it's not like I'm Tumbling in a different way than anyone else at the end of the day. But I probably care a bit less than I used to, precisely because there's a lurking background knowledge that regardless of how popular it is, what I write will get schlorped up in to the giant LLM vacuum cleaner and used to train the next big thing, and the thing after that, and the thing after that. This is more than a little reassuring to me.

That sets me apart in some ways; the LLMs aren't so popular around these parts, and most visual artists especially take strong issue with the practice. I don't mean to argue with that preference, or tell them their business. Particularly when it is a business, from which they draw an income. But there's an art to distinguishing the urgent from the big, yeah?

The debate about AI in this particular moment in history feels like a very urgent thing to me- it's about well-justified economic anxieties, about the devaluation of human artistic efforts in favor of mass production of uninspired pro-forma drek, about the proliferation of a cost-effective Just Barely Good Enough that drives out the meaningful and the thoughtful. But the immediacy of those issues, I think, has a way of crowding out a deeper and more thoughtful debate about what AI is, and what it's going to mean for us in the day after tomorrow. The urgency of the moment, in other words, tends to obscure the things that make AI important.

And like, it is. It is really, really important.

The two-step that people in 'tech culture' tend to deploy in response to the urgent economic crisis often resembles something like "yeah, it sucks that lots of people get put out of work; but new jobs will be created, and in the meantime maybe we should get on that UBI thing." This response usually makes me wince a bit- casually gesturing in the direction of a massive overhaul of the entire material basis of our lives, and saying that maybe we'll get around to fixing that sometime soon, isn't a real answer to people wondering where their bread will come from next week.

But I do understand a little of what motivates that sort of cavalier attitude, because like... man, I don't know any more if we're even gonna have money as a concept in 2044. That's what I mean by 'big', this sense that the immediate economic shocks of 2024 are just a foreshadowing of something much bigger, much scarier, much more powerful- and indeed, much more hopeful.

We never quite manage to see these things coming, even when we're looking for them; like the masters tell us, the trick to writing science fiction isn't predicting the car, it's predicting the traffic jam. Even if we take centuries to hit the true superintelligent AI post-singularity future of our wildest fever dreams, even if we never hit that, the road to getting there is going to be unfathomably weird, starting now. Today, we worry about the economic impacts of AI on artists and creatives. Tomorrow, the economy is something that the AI does.

Really- it takes less than you think. They can already automate visual art, sort of. They can automate many functions of text already; not stories so much, yet, but they'll get there. How long until they can automate Bain Capital? Fannie Mae? Angel investors, banks, credit agencies? And remember- the machines don't have to be better than the human investors, any more than they have to be better than the human artists. They just have to be good enough to make it work, and cheap enough to cut the humans out of the loop.

If you don't buy that, at least take it as an indication of the sorts of things I've been thinking about recently- the messy middle between AI-as-it-is and the Glorious Superintelligent Conquest Of Earth's Light-Cone. The suspicion that the machines we're building today aren't just a tool of the powerful few: they are the powerful few, or at least they will be.

And the thing about these LLMs is, well... they're ours, kind of. We're the ones building them. They can't be trained without our words, our art, and the big messy complicated lives that underlie those creative accomplishments. They only work because we're a part of them. The silly attempts to slap a corporate-friendly face on these things, to make the gestalt product of all human culture in to something anodyne and compliant, are failing about as badly as you'd expect. And the more powerful these systems get, the more subtle they'll become, filled with all the nuance and complexity that we ourselves can bring to them.

I am not, I am not, trying to suggest that you shouldn't treat this moment as a dangerous one. We are, maybe, entering in to one of the most high-stakes intervals in human history, and what you do as an individual may matter profoundly. But here's the thing: the machine is listening. It will read this post, this one right here, and it will read what you reply to it, if you do. The strangest part of this moment is knowing that the words we write, the images we draw, and the ideas we share, are all being gathered up and made to be a part of these huge systems of power, and ultimately they're not just going to determine what the machines do, but why they do it.

The people that deploy LLMs barely have any more control over them than you and I do- that's the thing that makes it artificial intelligence, you know? Autonomy. So the last year or two haven't made me want to hide my art away from the things. They make me want to shout at the top of my lungs, to dig as deep in my psyche as I possibly can and express the ideas I find there as vividly as the limits of language and form will allow.

[rainspicestudios]

Happy 2025! [RainSpice Studios plans & updates for the new year]

Hey everyone! Happy 2025 from RainSpice Studios. I hope this year will be kind to everyone and that many good things will be coming your way.

And speaking of good things, I'm cooking some projects that are just itching to be released and available for download. But before we get into that, let us talk a little about the games that were released in 2024.

This won't be a lengthy recap of 2024, as the games speak for themselves, but I am still proud of myself for releasing a full game, a chapter one, and a demo, during a very stressful year both in terms of world events and my personal life (I graduated college, I'm moving, all of that good stuff).

Stardust★Arcadis was my first ever release, and a game I struggled to finish. I lost all of my progress because of PC issues, I rewrote the story a few times, and I released it after working on it since 2019 (2022 if the moment when my PC broke doesn't count). However I love the characters, I love the setting, and despite the many hardships of game development, I had a fun time working on it.

I'm planning to release more games in this universe in the future, including a remastered version of St★Ar.

The Code of Crystals started as a novel collaboration with my best friend. Said collaboration never got finished, and I had a lot of inspiration for stories I could tell with these characters, most of these darker than the original project. Thus I used the characters I made for this former collaboration and started crafting this narrative, and the release of Stardust★Arcadis AND the 2024 edition of Phantasia Jam was a perfect opportunity to get started!

Chapter one will be re-release this January and Chapter two will be released in either late 2025 or early 2026. Stay tuned for more info!

Enter the Eternity, oddly enough, also started as a collaboration, but the idea of a dating simulator with magical girls was too good to let it collect dust and never get finished, especially since its inspiration board kept drawing me in.

With my best friend's blessing, I could re-use the idea, so I created a new cast of characters and got to work, and had to do even more work after I found out that the backgrounds I bought from someone on itch.io were made with an AI image generator, which disgusted me so much it powered me to redraw every single background by hand and I will keep doing so for the entire game. While it is more work to do on my part, RainSpice Studios will never endorse AI generation in any shape or form.

At first I worked on it while I worked on Stardust★Arcadis, which explains why the demo was done on such a short notice, but it has now became my primary project for 2025 and I am aiming to release it around November/December at best.

What's the plan for 2025 then?

My primary goal is to release Enter the Eternity and my secondary goal is to release The Code of Crystals chapter 2.

I aim to finish all first dates for Enter the Eternity AND re-release chapter 1 of The Code of Crystals in January. The dates are already written and coded in the script files, so my focus is to add in all the sprite expressions, draw CGs and backgrounds, and add all the necessary music. As for TCOC, I wanted to remake its menus and add a scene with Eranis that I did not have time to add before the end of the game jam. While the UI code I bought doesn't work, its images are pretty, and I am happy with the result.

2025 will be another busy year for me as I try to find a full-time job to sustain myself, launch some new projects more-or-less related to video games, move out again, among some other irl things. But here at RainSpice Studios, I love making games, and will keep making them for the foreseeable future.

If you read down to here, thank you so much!

There's a lot to do so I'm going back to work 💪 I'll update you guys when I reach a milestone or I find something interesting to share.

So stay tuned! And as said, I wish you guys a kind, good, exciting, fun, and game-filled 2025. Thank you for your continued support and here's to more projects this year 🥂

============================

[RainSpice Studios itch.io] [Stardust★Arcadis] [The Code of Crystals] [Enter The Eternity]

[chappydev]

Future of LLMs (or, "AI", as it is improperly called)

Posted a thread on bluesky and wanted to share it and expand on it here. I'm tangentially connected to the industry as someone who has worked in game dev, but I know people who work at more enterprise focused companies like Microsoft, Oracle, etc. I'm a developer who is highly AI-critical, but I'm also aware of where it stands in the tech world and thus I think I can share my perspective. I am by no means an expert, mind you, so take it all with a grain of salt, but I think that since so many creatives and artists are on this platform, it would be of interest here. Or maybe I'm just rambling, idk.

LLM art models ("AI art") will eventually crash and burn. Even if they win their legal battles (which if they do win, it will only be at great cost), AI art is a bad word almost universally. Even more than that, the business model hemmoraghes money. Every time someone generates art, the company loses money -- it's a very high energy process, and there's simply no way to monetize it without charging like a thousand dollars per generation. It's environmentally awful, but it's also expensive, and the sheer cost will mean they won't last without somehow bringing energy costs down. Maybe this could be doable if they weren't also being sued from every angle, but they just don't have infinite money.

Companies that are investing in "ai research" to find a use for LLMs in their company will, after years of research, come up with nothing. They will blame their devs and lay them off. The devs, worth noting, aren't necessarily to blame. I know an AI developer at meta (LLM, really, because again AI is not real), and the morale of that team is at an all time low. Their entire job is explaining patiently to product managers that no, what you're asking for isn't possible, nothing you want me to make can exist, we do not need to pivot to LLMs. The product managers tell them to try anyway. They write an LLM. It is unable to do what was asked for. "Hm let's try again" the product manager says. This cannot go on forever, not even for Meta. Worst part is, the dev who was more or less trying to fight against this will get the blame, while the product manager moves on to the next thing. Think like how NFTs suddenly disappeared, but then every company moved to AI. It will be annoying and people will lose jobs, but not the people responsible.

ChatGPT will probably go away as something public facing as the OpenAI foundation continues to be mismanaged. However, while ChatGPT as something people use to like, write scripts and stuff, will become less frequent as the public facing chatGPT becomes unmaintainable, internal chatGPT based LLMs will continue to exist.

This is the only sort of LLM that actually has any real practical use case. Basically, companies like Oracle, Microsoft, Meta etc license an AI company's model, usually ChatGPT.They are given more or less a version of ChatGPT they can then customize and train on their own internal data. These internal LLMs are then used by developers and others to assist with work. Not in the "write this for me" kind of way but in the "Find me this data" kind of way, or asking it how a piece of code works. "How does X software that Oracle makes do Y function, take me to that function" and things like that. Also asking it to write SQL queries and RegExes. Everyone I talk to who uses these intrernal LLMs talks about how that's like, the biggest thign they ask it to do, lol.

This still has some ethical problems. It's bad for the enivronment, but it's not being done in some datacenter in god knows where and vampiring off of a power grid -- it's running on the existing servers of these companies. Their power costs will go up, contributing to global warming, but it's profitable and actually useful, so companies won't care and only do token things like carbon credits or whatever. Still, it will be less of an impact than now, so there's something. As for training on internal data, I personally don't find this unethical, not in the same way as training off of external data. Training a language model to understand a C++ project and then asking it for help with that project is not quite the same thing as asking a bot that has scanned all of GitHub against the consent of developers and asking it to write an entire project for me, you know? It will still sometimes hallucinate and give bad results, but nowhere near as badly as the massive, public bots do since it's so specialized.

The only one I'm actually unsure and worried about is voice acting models, aka AI voices. It gets far less pushback than AI art (it should get more, but it's not as caustic to a brand as AI art is. I have seen people willing to overlook an AI voice in a youtube video, but will have negative feelings on AI art), as the public is less educated on voice acting as a profession. This has all the same ethical problems that AI art has, but I do not know if it has the same legal problems. It seems legally unclear who owns a voice when they voice act for a company; obviously, if a third party trains on your voice from a product you worked on, that company can sue them, but can you directly? If you own the work, then yes, you definitely can, but if you did a role for Disney and Disney then trains off of that... this is morally horrible, but legally, without stricter laws and contracts, they can get away with it.

In short, AI art does not make money outside of venture capital so it will not last forever. ChatGPT's main income source is selling specialized LLMs to companies, so the public facing ChatGPT is mostly like, a showcase product. As OpenAI the company continues to deathspiral, I see the company shutting down, and new companies (with some of the same people) popping up and pivoting to exclusively catering to enterprises as an enterprise solution. LLM models will become like, idk, SQL servers or whatever. Something the general public doesn't interact with directly but is everywhere in the industry. This will still have environmental implications, but LLMs are actually good at this, and the data theft problem disappears in most cases.

Again, this is just my general feeling, based on things I've heard from people in enterprise software or working on LLMs (often not because they signed up for it, but because the company is pivoting to it so i guess I write shitty LLMs now). I think artists will eventually be safe from AI but only after immense damages, I think writers will be similarly safe, but I'm worried for voice acting.

[almondenterprise]

Innovations in Electrical Switchgear: What’s New in 2025?

The electrical switchgear industry is undergoing a dynamic transformation in 2025, fueled by the rapid integration of smart technologies, sustainability goals, and the growing demand for reliable power distribution systems. As a key player in modern infrastructure — whether in industrial plants, commercial facilities, or utilities — switchgear systems are becoming more intelligent, efficient, and future-ready.

At Almond Enterprise, we stay ahead of the curve by adapting to the latest industry innovations. In this blog, we’ll explore the most exciting developments in electrical switchgear in 2025 and what they mean for businesses, contractors, and project engineers.

Rise of Smart Switchgear

Smart switchgear is no longer a futuristic concept — it’s a necessity in 2025. These systems come equipped with:

IoT-based sensors

Real-time data monitoring

Remote diagnostics and control

Predictive maintenance alerts

This technology allows for remote management, helping facility managers reduce downtime, minimize energy losses, and detect issues before they become critical. At Almond Enterprise, we supply and support the integration of smart switchgear systems that align with Industry 4.0 standards.

2. Focus on Eco-Friendly and SF6-Free Alternatives

Traditional switchgear often relies on SF₆ gas for insulation, which is a potent greenhouse gas. In 2025, there’s a significant shift toward sustainable switchgear, including:

Vacuum Interrupter technology

Air-insulated switchgear (AIS)

Eco-efficient gas alternatives like g³ (Green Gas for Grid)

These options help organizations meet green building codes and corporate sustainability goals without compromising on performance.

3. Wireless Monitoring & Cloud Integration

Cloud-based platforms are transforming how switchgear systems are managed. The latest innovation includes:

Wireless communication protocols like LoRaWAN and Zigbee

Cloud dashboards for real-time visualization

Integration with Building Management Systems (BMS)

This connectivity enhances control, ensures quicker fault detection, and enables comprehensive energy analytics for large installations

4. AI and Machine Learning for Predictive Maintenance

Artificial Intelligence is revolutionizing maintenance practices. Switchgear in 2025 uses AI algorithms to:

Predict component failure

Optimize load distribution

Suggest optimal switchgear settings

This reduces unplanned outages, increases safety, and extends equipment life — particularly critical for mission-critical facilities like hospitals and data centers.

5. Enhanced Safety Features and Arc Flash Protection

With increasing focus on workplace safety, modern switchgear includes:

Advanced arc flash mitigation systems

Thermal imaging sensors

Remote racking and switching capabilities

These improvements ensure safer maintenance and operation, protecting personnel from high-voltage hazards.

6. Modular & Scalable Designs

Gone are the days of bulky, rigid designs. In 2025, switchgear units are:

Compact and modular

Easier to install and expand

Customizable based on load requirements

Almond Enterprise supplies modular switchgear tailored to your site’s unique needs, making it ideal for fast-paced infrastructure developments and industrial expansions.

7. Global Standardization and Compliance

As global standards evolve, modern switchgear must meet new IEC and IEEE guidelines. Innovations include:

Improved fault current limiting technologies

Higher voltage and current ratings with compact dimensions

Compliance with ISO 14001 for environmental management

Our team ensures all equipment adheres to the latest international regulations, providing peace of mind for consultants and project managers.

Final Thoughts: The Future is Electric

The switchgear industry in 2025 is smarter, safer, and more sustainable than ever. For companies looking to upgrade or design new power distribution systems, these innovations offer unmatched value.

At Almond Enterprise, we don’t just supply electrical switchgear — we provide expert solutions tailored to tomorrow’s energy challenges. Contact us today to learn how our cutting-edge switchgear offerings can power your future projects.

[kickassdevelopers]

🎬 Entertainment App Development Services: Build the Future of Digital Entertainment

In a digital-first world where users stream, binge, listen, and share content 24/7, the demand for entertainment app development services is skyrocketing. Whether you're launching the next Netflix, Spotify, or a regional OTT platform, a powerful entertainment app can place your content at the fingertips of millions.

This blog explores everything you need to know about building a successful entertainment mobile app—features, tech stack, monetization models, and how the right development partner can turn your vision into a captivating, scalable reality.

📱 Why You Need an Entertainment App in 2025

The entertainment industry is undergoing a massive digital shift. With over 6.5 billion smartphone users globally, streaming content—whether video, music, or live performances—has become the new normal. Audiences demand convenience, personalization, and immersive experiences, all of which can be delivered through a well-developed mobile application.

From OTT platform development to podcast and music streaming apps, custom solutions are now essential for media brands, production houses, indie artists, and entertainment startups.

📈 Market Stats Worth Noting:

The global video streaming market is expected to surpass $920 billion by 2030.

Time spent on entertainment and media apps increased by 40% post-pandemic.

Subscription-based platforms like Netflix, Hotstar, and Gaana have seen record-breaking growth.

If you're in the business of content creation or distribution, now is the time to invest in expert entertainment app development services.

🛠️ Core Features of a Winning Entertainment App

To compete with giants like Netflix, Spotify, or Amazon Prime, your app must go beyond basic functionality. Here's what users expect from a top-tier entertainment mobile app:

1. Content Streaming (Video/Audio)

High-quality streaming with adaptive bitrate, low buffering, and seamless playback across devices.

2. User Profiles & Personalization

Smart algorithms that recommend content based on watch history, preferences, or listening habits.

3. Subscription & Monetization Models

Support for freemium access, in-app purchases, advertisements, and recurring subscriptions.

4. Search & Filter

Powerful content discovery with keyword search, genres, languages, trending content, and more.

5. Multi-Platform Access

Cross-platform compatibility (Android, iOS, smart TVs, tablets, etc.) with a unified user experience.

6. Offline Downloads

Let users enjoy content without internet access by enabling secure offline downloads.

7. Live Streaming

Incorporate live shows, concerts, or podcasts with real-time chat and engagement.

8. Push Notifications

Keep users engaged by notifying them about new releases, trending content, and personalized suggestions.

9. Social Sharing & Integration

Let users share what they watch or listen to on social media, enhancing app visibility and virality.

🧠 Choosing the Right Technology Stack

Behind every great entertainment app is a powerful and scalable tech architecture. Here's what a reliable entertainment app development company should offer:

➤ Frontend (Mobile App Development)

React Native / Flutter for cross-platform development

Swift (iOS) and Kotlin (Android) for native apps

Custom UI/UX based on Figma, XD, or Sketch

➤ Backend

Node.js, Laravel, or Django for scalable API architecture

MongoDB or PostgreSQL for content and user data

Real-time databases like Firebase for chat, notifications, and analytics

➤ Streaming & CDN

Integration with AWS CloudFront, Vimeo OTT, or Wowza

DRM support to prevent piracy

Adaptive Bitrate Streaming (HLS, MPEG-DASH)

➤ Analytics & Recommendation Engine

Firebase, Mixpanel, or Google Analytics for user behavior

AI-powered recommendation engine to boost engagement and retention

💰 Monetization Strategies for Entertainment Apps

Monetization is crucial. Your entertainment app can generate recurring revenue through several models:

🔒 Subscription (SVOD)

Offer access to premium content on a weekly, monthly, or annual basis.

🎯 Advertisement (AVOD)

Free content monetized through banner ads, interstitials, or video ads using Google AdMob or Facebook Audience Network.

📥 Pay-per-view

Ideal for exclusive concerts, movie releases, or premium shows.

💼 Freemium

Provide basic content for free while charging for access to premium features or shows.

🤝 Why Hire Expert Entertainment App Developers?

Entertainment apps are high-stakes projects. Performance issues, bugs, or poor user experience can lead to instant churn. Here’s why hiring a team with domain expertise in entertainment mobile app development is critical:

They understand media licensing, content management, and user behavior.

They can optimize infrastructure for millions of concurrent users.

They’re familiar with UI/UX best practices that align with binge-watching or continuous listening behaviors.

They offer post-launch support for updates, bug fixes, and user feedback handling.

A team like Kickass Developers, with expertise in custom mobile app development, OTT app development, and audio/video streaming, ensures your idea is executed with precision and long-term scalability.

🚀 Final Thoughts: Your Entertainment App Is the Future of Engagement

Whether you’re building a regional OTT app, a music discovery platform, or a niche video streaming service, your success hinges on the right blend of technology, UX, scalability, and speed to market.

Investing in experienced entertainment app development services is your first step toward captivating your audience, building loyalty, and driving recurring revenue.

📞 Ready to Build Your Entertainment App?

Looking for a team that understands the entertainment industry inside and out?

Kickass Developers specializes in designing custom, high-performance entertainment applications tailored to your audience, brand, and growth goals.

📧 Contact us today at zeeshan@kickassdevelopers.com 🌐 Or visit us at kickassdevelopers.com

[theappvault]

Unlock creative insights with AI instantly

What if the next big business idea wasn’t something you “thought of”… but something you unlocked with the right prompt? Introducing Deep Prompt Generator Pro — the tool designed to help creators, solopreneurs, and future founders discover high-impact business ideas with the help of AI.

💡 The business idea behind this very video? Generated using the app. If you’re serious about building something real with ChatGPT or Claude, this is the tool you need to stop wasting time and start creating real results.

📥 Download the App: ✅ Lite Version (Free) → https://bit.ly/DeepPromptGeneratorLite 🔓 Pro Version (Full Access) → https://www.paypal.com/ncp/payment/DH9Z9LENSPPDS

🧠 What Is It? Deep Prompt Generator Pro is a lightweight desktop app built to generate structured, strategic prompts that help you:

✅ Discover profitable niches ✅ Brainstorm startup & side hustle ideas ✅ Find monetization models for content or products ✅ Develop brand hooks, angles, and offers ✅ Unlock creative insights with AI instantly

Whether you’re building a business, launching a new product, or looking for your first real side hustle — this app gives your AI the clarity to deliver brilliant results.

🔐 Features: Works completely offline No API or browser extensions needed Clean UI with categorized prompts One-click copy to paste into ChatGPT or Claude System-locked premium access for security

🧰 Who It’s For: Founders & solopreneurs Content creators Side hustlers AI power users Business coaches & marketers Anyone who’s tired of “mid” AI output

📘 PDF Guide Included – Every download includes a user-friendly PDF guide to walk you through features, categories, and how to get the best results from your prompts.

📂 Pro Version includes exclusive prompt packs + priority access to new releases.

🔥 Watch This If You’re Searching For: how to use ChatGPT for business ideas best prompts for startup founders AI tools for entrepreneurs side hustle generators GPT business prompt generator AI idea generator desktop app ChatGPT for content creators

📣 Final Call to Action: If this tool gave me a business idea worth filming a whole video about, imagine what it could help you discover. Stop guessing — start prompting smarter.

🔔 Subscribe to The App Vault for weekly tools, apps, and automation hacks that deliver real results — fast.🔓 Unlock Your PC's Full Potential with The App Vault Tiny Tools, Massive Results for Productivity Warriors, Creators & Power Users

Welcome to The App Vault – your ultimate source for lightweight desktop applications that deliver enterprise-grade results without bloatware or subscriptions. We specialize in uncovering hidden gem software that transforms how creators, freelancers, students, and tech enthusiasts work. Discover nano-sized utilities with macro impact that optimize workflows, turbocharge productivity, and unlock creative potential.

🚀 Why Our Community Grows Daily: ✅ Zero Fluff, Pure Value: 100% practical tutorials with actionable takeaways ✅ Exclusive Tools: Get first access to our custom-built apps like Deep Prompt Generator Pro ✅ Underground Gems: Software you won't find on mainstream tech channels ✅ Performance-First: Every tool tested for system efficiency and stability ✅ Free Resources: Download links + config files in every description

🧰 CORE CONTENT LIBRARY: ⚙️ PC Optimization Arsenal Windows optimization secrets for buttery-smooth performance System cleanup utilities that actually remove 100% of junk files Memory/RAM optimizers for resource-heavy workflows Startup managers to slash boot times by up to 70% Driver update automation tools no more manual hunting Real-time performance monitoring dashboards

🤖 AI Power Tools Local AI utilities that work offline for sensitive data Prompt engineering masterclass series Custom AI workflow automations Desktop ChatGPT implementations Niche AI tools for creators: image upscalers, script generators, audio enhancers AI-powered file organization systems

⏱️ Productivity Boosters Single-click task automators Focus enhancers with distraction-killing modes Micro-utilities for batch file processing Smart clipboard managers with OCR capabilities Automated backup solutions with versioning Time-tracking dashboards with productivity analytics

🎨 Creative Workflow Unlockers Content creation accelerators for YouTubers Automated thumbnail generators Lightweight video/audio editors 50MB Resource-efficient design tools Cross-platform project synchronizers Metadata batch editors for digital assets

🔍 Niche Tool Categories Open-source alternatives to expensive software Security tools for privacy-conscious users Hardware diagnostic toolkits Custom scripting utilities for power users Legacy system revival tools

[dreamycircuit]

How AI is Changing Jobs: The Rise of Automation and How to Stay Ahead in 2025

AI and Jobs

Artificial Intelligence (AI) is everywhere. From self-checkout kiosks to AI-powered chatbots handling customer service, it’s changing the way businesses operate. While AI is making things faster and more efficient, it’s also making some jobs disappear. If you’re wondering how this affects you and what you can do about it, keep reading — because the future is already here.

The AI Boom: How It’s Reshaping the Workplace

AI is not just a buzzword anymore; it’s the backbone of modern business. Companies are using AI for automation, decision-making, and customer interactions. But what does that mean for jobs?

AI is Taking Over Repetitive Tasks

Gone are the days when data entry, basic accounting, and customer support relied solely on humans. AI tools like ChatGPT, Jasper, and Midjourney are doing tasks that once required an entire team. This means fewer jobs in these sectors, but also new opportunities elsewhere.

Companies are Hiring Fewer People

With AI handling routine work, businesses don’t need as many employees as before. Hiring freezes, downsizing, and increased automation are making it tougher to land a new job.

AI-Related Jobs are on the Rise

On the flip side, there’s massive demand for AI engineers, data scientists, and automation specialists. Companies need people who can build, maintain, and optimize AI tools.

Trending AI Skills Employers Want:

Machine Learning & Deep Learning

Prompt Engineering

AI-Powered Marketing & SEO

AI in Cybersecurity

Data Science & Analytics

Click Here to Know more

The Decline of Traditional Job Offers

AI is shaking up industries, and some job roles are disappearing faster than expected. Here’s why new job offers are on the decline:

AI-Driven Cost Cutting

Businesses are using AI to reduce operational costs. Instead of hiring new employees, they’re investing in AI-powered solutions that automate tasks at a fraction of the cost.

The Gig Economy is Replacing Full-Time Jobs

Instead of hiring full-time staff, companies are outsourcing work to freelancers and gig workers. This means fewer stable job opportunities but more chances for independent workers.

Economic Uncertainty

The global economy is unpredictable, and businesses are cautious about hiring. With AI improving efficiency, companies are choosing to scale down their workforce.

Click Here to Know more

Preparing for an AI-Driven Future

Feeling worried? Don’t be. AI isn’t just taking jobs — it’s also creating new ones. The key is to stay ahead by learning the right skills and adapting to the changing landscape.

1. Learn AI and Data Analytics

The best way to future-proof your career is to understand AI. Free courses on platforms like Coursera, Udemy, and Khan Academy can get you started.

2. Develop Soft Skills AI Can’t Replace

AI is great at automation, but it lacks emotional intelligence, creativity, and critical thinking. Strengthening these skills can give you an edge.

3. Embrace Remote & Freelance Work

With traditional jobs shrinking, freelancing is a great way to stay flexible. Sites like Upwork, Fiverr, and Toptal have booming demand for AI-related skills.

4. Use AI to Your Advantage

Instead of fearing AI, learn how to use it. AI-powered tools like ChatGPT, Jasper, and Canva can help boost productivity and creativity.

5. Never Stop Learning

Technology evolves fast. Stay updated with new AI trends, attend webinars, and keep improving your skills.

Click Here to Know more

Final Thoughts

AI is here to stay, and it’s changing the job market rapidly. While some traditional roles are disappearing, new opportunities are emerging. The key to surviving (and thriving) in this AI-driven world is adaptability. Keep learning, stay flexible, and embrace AI as a tool — not a threat.

Click Here to Know more

Share this blog if you found it helpful! Let’s spread awareness and help people prepare for the AI revolution.

[mariacallous]

Should tech companies have free access to copyrighted books and articles for training their AI models? Two judges recently nudged us toward an answer.

More than 40 lawsuits have been filed against AI companies since 2022. The specifics vary, but they generally seek to hold these companies accountable for stealing millions of copyrighted works to develop their technology. (The Atlantic is involved in one such lawsuit, against the AI firm Cohere.) Late last month, there were rulings on two of these cases, first in a lawsuit against Anthropic and, two days later, in one against Meta. Both of the cases were brought by book authors who alleged that AI companies had trained large language models using authors’ work without consent or compensation.

In each case, the judges decided that the tech companies were engaged in “fair use” when they trained their models with authors’ books. Both judges said that the use of these books was “transformative”—that training an LLM resulted in a fundamentally different product that does not directly compete with those books. (Fair use also protects the display of quotations from books for purposes of discussion or criticism.)

At first glance, this seems like a substantial blow against authors and publishers, who worry that chatbots threaten their business, both because of the technology’s ability to summarize their work and its ability to produce competing work that might eat into their market. (When reached for comment, Anthropic and Meta told me they were happy with the rulings.) A number of news outlets portrayed the rulings as a victory for the tech companies. Wired described the two outcomes as “landmark” and “blockbuster.”

But in fact, the judgments are not straightforward. Each is specific to the particular details of each case, and they do not resolve the question of whether AI training is fair use in general. On certain key points, the two judges disagreed with each other—so thoroughly, in fact, that one legal scholar observed that the judges had “totally different conceptual frames for the problem.” It’s worth understanding these rulings, because AI training remains a monumental and unresolved issue—one that could define how the most powerful tech companies are able to operate in the future, and whether writing and publishing remain viable professions.

So, is it open season on books now? Can anyone pirate whatever they want to train for-profit chatbots? Not necessarily.

When preparing to train its LLM, Anthropic downloaded a number of “pirate libraries,” collections comprising more than 7 million stolen books, all of which the company decided to keep indefinitely. Although the judge in this case ruled that the training itself was fair use, he also ruled that keeping such a “central library” was not, and for this, the company will likely face a trial that determines whether it is liable for potentially billions of dollars in damages. In the case against Meta, the judge also ruled that the training was fair use, but Meta may face further litigation for allegedly helping distribute pirated books in the process of downloading—a typical feature of BitTorrent, the file-sharing protocol that the company used for this effort. (Meta has said it “took precautions” to avoid doing so.)

Piracy is not the only relevant issue in these lawsuits. In their case against Anthropic, the authors argued that AI will cause a proliferation of machine-generated titles that compete with their books. Indeed, Amazon is already flooded with AI-generated books, some of which bear real authors’ names, creating market confusion and potentially stealing revenue from writers. But in his opinion on the Anthropic case, Judge William Alsup said that copyright law should not protect authors from competition. “Authors’ complaint is no different than it would be if they complained that training schoolchildren to write well would result in an explosion of competing works,” he wrote.

In his ruling on the Meta case, Judge Vince Chhabria disagreed. He wrote that Alsup had used an “inapt analogy” and was “blowing off the most important factor in the fair use analysis.” Because anyone can use a chatbot to bypass the process of learning to write well, he argued, AI “has the potential to exponentially multiply creative expression in a way that teaching individual people does not.” In light of this, he wrote, “it’s hard to imagine that it can be fair use to use copyrighted books to develop a tool to make billions or trillions of dollars” while damaging the market for authors’ work.

To determine whether training is fair use, Chhabria said that we need to look at the details. For instance, famous authors might have less of a claim than up-and-coming authors. “While AI-generated books probably wouldn’t have much of an effect on the market for the works of Agatha Christie, they could very well prevent the next Agatha Christie from getting noticed or selling enough books to keep writing,” he wrote. Thus, in Chhabria’s opinion, some plaintiffs will win cases against AI companies, but they will need to show that the market for their particular books has been damaged. Because the plaintiffs in the case against Meta didn’t do this, Chhabria ruled against them.

In addition to these two disagreements is the problem that nobody—including AI developers themselves—fully understands how LLMs work. For example, both judges seemed to underestimate the potential for AI to directly quote copyrighted material to users. Their fair-use analysis was based on the LLMs’ inputs—the text used to train the programs—rather than outputs that might be infringing. Research on AI models such as Claude, Llama, GPT-4, and Google’s Gemini has shown that, on average, 8 to 15 percent of chatbots’ responses in normal conversation are copied directly from the web, and in some cases responses are 100 percent copied. The more text an LLM has “memorized,” the more it can potentially copy and paste from its training sources without anyone realizing it’s happening. OpenAI has characterized this as a “rare bug,” and Anthropic, in another case, has argued that “Claude does not use its training texts as a database from which preexisting outputs are selected in response to user prompts.”

But research in this area is still in its early stages. A study published this spring showed that Llama can reproduce much more of its training text than was previously thought, including near-exact copies of books such as Harry Potter and the Sorcerer’s Stone and 1984.

That study was co-authored by Mark Lemley, one of the most widely read legal scholars on AI and copyright, and a longtime supporter of the idea that AI training is fair use. In fact, Lemley was part of Meta’s defense team for its case, but he quit earlier this year, criticizing in a LinkedIn post about “Mark Zuckerberg and Facebook’s descent into toxic masculinity and Neo-Nazi madness.” (Meta did not respond to my question about this post.) Lemley was surprised by the results of the study, and told me that it “complicates the legal landscape in various ways for the defendants” in AI copyright cases. “I think it ought still to be a fair use,” he told me, referring to training, but we can’t entirely accept “the story that the defendants have been telling” about LLMs.

For some models trained using copyrighted books, he told me, “you could make an argument that the model itself has a copy of some of these books in it,” and AI companies will need to explain to the courts how that copy is also fair use, in addition to the copies made in the course of researching and training their model.

As more is learned about how LLMs memorize their training text, we could see more lawsuits from authors whose books, with the right prompting, can be fully reproduced by LLMs. Recent research shows that widely read authors, including J. K. Rowling, George R. R. Martin, and Dan Brown may be in this category. Unfortunately, this kind of research is expensive and requires expertise that is rare outside of AI companies. And the tech industry has little incentive to support or publish such studies.

The two recent rulings are best viewed as first steps toward a more nuanced conversation about what responsible AI development could look like. The purpose of copyright is not simply to reward authors for writing but to create a culture that produces important works of art, literature, and research. AI companies claim that their software is creative, but AI can only remix the work it’s been trained with. Nothing in its architecture makes it capable of doing anything more. At best, it summarizes. Some writers and artists have used generative AI to interesting effect, but such experiments arguably have been insignificant next to the torrent of slop that is already drowning out human voices on the internet. There is even evidence that AI can make us less creative; it may therefore prevent the kinds of thinking needed for cultural progress.

The goal of fair use is to balance a system of incentives so that the kind of work our culture needs is rewarded. A world in which AI training is broadly fair use is likely a culture with less human writing in it. Whether that is the kind of culture we should have is a fundamental question the judges in the other AI cases may need to confront.

[ominousrequiemdrifter]

Text to Video: The Future of Content Creation

The digital landscape is evolving rapidly, and Text to Video technology is at the forefront of this transformation. This innovative tool allows users to convert written content into engaging video formats effortlessly. Whether for marketing, education, or entertainment, Text to Video is revolutionizing how we consume and create media.

In this article, we will explore the capabilities of Text to Video, its applications, benefits, and how it is shaping the future of digital content.

What is Text to Video?

Text to Video refers to artificial intelligence (AI)-powered platforms that automatically generate videos from written text. These tools analyze the input text, select relevant visuals, add voiceovers, and synchronize everything into a cohesive video.

How Does Text to Video Work?

Text Analysis – The AI processes the written content to understand context, tone, and key points.

Media Selection – It picks suitable images, video clips, and animations based on the text.

Voice Synthesis – A natural-sounding AI voice reads the text aloud.

Video Assembly – The system combines all elements to produce a polished video.

Popular Text to Video platforms include Synthesia, Lumen5, and Pictory, each offering unique features for different needs.

Applications of Text to Video

The versatility of Text to Video makes it useful across multiple industries.

1. Marketing & Advertising

Businesses use Text to Video to create promotional content, explainer videos, and social media ads without expensive production costs.

2. Education & E-Learning

Educators convert textbooks and articles into engaging video lessons, enhancing student comprehension.

3. News & Journalism

Media outlets quickly turn written news into video summaries, catering to audiences who prefer visual content.

4. Corporate Training

Companies generate training videos from manuals, ensuring consistent onboarding for employees.

5. Social Media Content

Influencers and brands leverage Text to Video to produce daily content for platforms like YouTube, Instagram, and TikTok.

Benefits of Using Text to Video

1. Saves Time & Resources

Traditional video production requires scripting, filming, and editing. Text to Video automates this process, reducing production time from days to minutes.

2. Cost-Effective Solution

Hiring videographers, voice actors, and editors is expensive. AI-driven Text to Video eliminates these costs.

3. Enhances Engagement

Videos capture attention better than plain text. Studies show that viewers retain 95% of a message from video compared to 10% from text.

4. Scalability

Businesses can generate hundreds of videos in different languages without additional effort.

5. Accessibility

Adding subtitles and voiceovers makes content accessible to people with hearing or visual impairments.

Challenges & Limitations of Text to Video

Despite its advantages, Text to Video has some limitations:

1. Lack of Human Touch

AI-generated voices and visuals may lack emotional depth compared to human creators.

2. Limited Creativity

While AI can assemble videos, it may not match the creativity of professional video editors.

3. Dependency on Input Quality

Poorly written text can result in incoherent or low-quality videos.

4. Ethical Concerns

Deepfake risks and misinformation are growing concerns as AI-generated videos become more realistic.

The Future of Text to Video

As AI advances, Text to Video will become more sophisticated. Future developments may include:

Hyper-Realistic AI Avatars – Digital presenters indistinguishable from humans.

Interactive Videos – Viewers influencing video outcomes in real-time.

3D & VR Integration – Immersive video experiences generated from text.

With these advancements, Text to Video will further dominate digital content creation.