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floatingcatacombs · 5 months

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Patlabor is On Lock

12 Days of Aniblogging 2023, Day 3

While Gundam is the most recognizable mecha anime I got into this year, most of my time was really spent working my way through the Patlabor franchise, and it’s quickly become one of my favorites. I’ve always loved the quiet moments in mecha shows, which makes sense considering I started with Macross and live for the bridge bunny gossip and off-duty downtown hangouts. Patlabor is built with this downtime at its core, operating with more of a slice of life mentality than anything else.

A lovable cast is crucial for making this work. Thankfully, Noa Izumi is a wonderful and unique protagonist, a scrappy soft butch who’s in it for the eroticism of the machine. The first Patlabor opening is a love letter from Noa to her mecha, and I get it! The AV-98 Ingram is an iconic design, with its asymmetric bunny ear antennae and shoulder lights and comically oversized revolver that requires the right hand to pop out in order to draw, exposing the arm wiring in the process. This is a show clearly written by first-generation mecha otaku, and plenty of time is dedicated to showing how the Labors have to be transported and recharged, how the movement software depends on reinforcement learning, showing off corporate model revisions, and of course repairs in the hangar.

Going back to the human characters, Noa’s work partner Asuma is clearly the more passive one within their dynamic, and it’s sweet to see that played out sincerely. And then there’s Kanuka Clancy, the stern weirdo badass from New York who’s constantly swearing and dropping one-liners in English. She’s the obvious breakthrough character of the show, and also the perfect opposites-attract pairing for Noa if you’re the kind of person whose yuri meter went off the charts during their drinking contest episode. Most of Patlabor’s cast seem fairly one-note at first, and one of the great tricks of the show is giving them just a little bit more depth than you would expect. Pretty much everyone, even the most jokey characters, eventually get a standalone episode or two that further sketches them out and offers real interiority. Captain Goto is another fan-favorite, and it’s definitely his mixture of laziness and wicked perceptiveness that does it, plus his main character billing in the movies.

SV2 may be a law enforcement unit, but this really isn’t a police procedural at the end of the day. These guys are the bum department out in the sticks who everyone hates, and the upside of that is that SV2 gets stuck with the oddest of jobs instead of cop work. Sometimes that’s dealing with a runaway military prototype, other times it’s arguing with the insurance company. The best kind of episodes are the ones that take almost entirely on base as everyone tries to solve a problem of their own making, like an Ingram falling into the sea or the mechanics getting into a fight with the only restaurant that delivers to them.

A main plot does eventually emerge, with a shadowy company developing a mysterious jet-black Labor piloted by a child who is the girlish boy to Noa Izumi’s boyish girl. The Griffon is sleek and curvy and has superiority in the water and air – it’s a machine designed to defeat Ingrams, and I wouldn’t be surprised if Yoji Shinkawa looked here when designing Metal Gear RAY. Automation is a fundamental ideological enemy of mecha – faceless mass production and artificial intelligence mean an end to the era of personal combat. Even Patlabor, a warless series, dips its toes into this idea in the later episodes, with Noa and the mechanics alike worrying that the neural networks in their new Labor models will make them redundant.

Overall, this show is hilarious and sweet and clearly loved by an older generation of otaku. So why didn’t I hear about it earlier? Partly it’s on me for not hanging out with the right mecha fans online for a while. But if I had to guess, it’s also because Patlabor is one of those works that’s straightforwardly, unobjectionably good in a way where it already says everything there is to be said about it. You can have near-infinite arguments about Zeon ideology or mobile suit powerscaling online, but there’s only so many times you can say “yeah, Noa Izumi, love that girl” precisely because everyone agrees. It can also be hard to pitch things by their vibes in a genre known for adrenaline and intrigue. Patlabor’s vibes, for the record, are immaculate.

I'm probably gonna be chasing the high of cel-era sunsets forever

Mecha’s also a bit looked down upon from the outside. Anything that makes it into the larger conversation has to be understood as “elevated” or a “genre deconstruction”, even if the very first Mobile Suit Gundam is already about Amuro’s trauma and PTSD from being made into a child soldier. This elevation is actually happening to the second Patlabor movie as we speak - it’s becoming increasingly discussed as a major component of Mamoru Oshii’s filmography, divorced from its source series and instead compared to his subsequent Ghost in the Shell movie. Funnily enough, Oshii’s contributions to the Patlabor TV show are actually the more lighthearted gag episodes.

A lot of recent Patlabor retrospectives have drawn attention to the artist’s collective Headgear, established and owned by the series creators so they would be able to retain the rights for the franchise. This structure is fairly unique for the anime industry and probably only makes sense for established creatives, but it does seem to have worked out great for them, providing financial stability and strong creative control over the franchise. This allowed Patlabor to thrive in the relative wasteland of late 80s TV anime, a time when even Gundam had fled to the OVA market.

That being said, it does take Patlabor switching back to OVAs to truly spread its wings. The New Files are a conclusion and continuation of the TV series that are willing to move at their own pace, resulting in some dramatic and surprisingly thoughtful stories. It’s genuinely touching to watch Goto and Nagumo try and fail to communicate their feelings for one another in a very restrained episode as thick with long-stewing emotions as it is empty space. Of course, the very next episode has half the cast get stuck in the sewer labyrinth underneath their base and there’s a bunch of Wizardry references. Oh, Oshii.

The Patlabor movies fully lean into this melancholy and uncertainty, and it’s a welcome evolution for the series. The first movie still ends with an all-out action set piece in a half-built mecha factory that stands in for the Tower of Babel, but the second one stays serious the whole time through, going as far as pivoting to a more realistic artsyle. It’s a challenging film. The politics are all-encompassing but fairly straightforward, as Oshii effectively infodumps a presentation on the postwar history of the JSDF throughout. Instead, what the makes the movie so difficult is its willingness to face the end of an era – the Cold War is over, the bubble economy has popped, and the former members of SV2 have all gone their separate ways. The conditions that have created Patlabor, both internal and external to the show, have dissipated. And the movie makes it clear by having the military stage a raid on SV2’s headquarters, tearing their Labors to shreds with gunfire in a beautifully animated act of desecration.

After watching her be a lovable mecha dweeb for 50 episodes, it hurts a bit to hear Noa Izumi say that she doesn’t want to be that girl obsessed with robots for the rest of her life! These characters are growing in such a way that will remove them from the focus of the narrative, and it’s a movie about letting go just as much as it is about looking towards an uncertain personal and national future. I love Miyazaki’s Porco Rosso, but the fact that Oshii put this out just one year later paints a delicious contrast between the two directors with regards to escapism versus reality with regards to militarism. There's some great interviews from the era where they're just taking potshots at each other about all this.

#12 days of anime #patlabor

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orossii · 2 years

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leftists suffer so immensely from the tendency to terminate critical thought based on whether or not a certain idea is culturally characterized as right wing or not. i saw some people on twitter suggest that being opposed to exposing children to age-inappropriate sexual content under the guise of promoting LGBTQ rights or feminism is wrong because it’s a talking point that’s frequently used by right wing reactionaries, and like. sure. but where leftists get extremely alienating to normal, everyday people and end up ultimately pushing them to the right is that instead of taking a stance that takes into account why so many people are so invested in safeguarding children from adult sexuality (one being the prevalence of child sexual abuse that a disturbingly high percentage of the population, esp women and girls, have had some level of personal experience with) and coming up with a reasonable solution to that problem that both protects children and de-couples peoples perception of gay rights and feminism from predatory behavior, the left chooses instead to go hard in the other direction by suggesting that it’s actively a good thing for children to be exposed to adult sexuality in the form of drag shows and sex ed curricula that promotes BDSM to 14-year-olds. if they’re not doing that they deny that it’s happening at all despite the right being all too eager to capitalize on the abundance of evidence that it very much is. just because YOU have decided it’s a form of thought crime to read what the right/center/heterodox left is saying about your cause and believe that questioning your worldview is violence, that doesn’t mean the people you’re trying to win over aren’t engaging with those arguments. you will need to know how to engage with what they’re seeing in an honest way that doesn’t make you look like you have something to hide, and if they have serious questions that you can’t answer without resorting to attacks on their character maybe that’s a you-problem and not a them-problem

it’s fucking embarrassing seeing this shit coming from people who self-ID as marxists. this is a big part of why post-epstein so many of the people rallying against child sexual abuse by the ruling capitalist elites, an issue with massive mobilization potential that’s just being completely dismissed by the left for the most part, are being herded toward right wing political impotence. this applies to so many other points too. serious marxists need to cut it the fuck out with the hardcore personal identification with leftism and realize that so much of what’s considered ‘progressive’ in the west is coming not from the working class, but the ruling class in the form of academia, big pharma, the military, intelligence circles, and the NGO industrial complex. capitalism is extremely flexible-- it can easily re-shape itself to be perfectly in-line with hyper-sectarian liberal identity politics when convenient and then quickly re-configure back to conservatism following the inevitable right wing cultural backlash. theoretically it can go on like that in cycles until world imperialism implodes upon itself. lots of people who consider themselves ‘progressives’ are enthusiastically supporting the US-proxy war in ukraine right now. the only thing that ultimately matters to the ruling class is capitalizing on whatever ideology allows them to proceed with business as usual for the imperial war and debt machine, and so-called progressive liberalism has been a fantastic boon in that department. we don’t win until we stop using ideology as a shortcut for moral superiority and start organizing with reality in mind even if we find it personally uncomfortable to reckon with

#womens and gay/gnc rights and racial justice are important mind you but those are achieved via materialist strategy and not baseless dogma #if you try to achieve any of the above solely culturally w/o targeting the economic base #you're gonna fall flat on your face #leftists tend to think of themselves as more moral and enlightened than the masses and their elitism is their downfall

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jcmarchi · 5 months

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Open-Source Platform Cuts Costs for Running AI - Technology Org

New Post has been published on https://thedigitalinsider.com/open-source-platform-cuts-costs-for-running-ai-technology-org/

Open-Source Platform Cuts Costs for Running AI - Technology Org

Cornell researchers have released a new, open-source platform called Cascade that can run artificial intelligence (AI) models in a way that slashes expenses and energy costs while dramatically improving performance.

Artificial intelligence hardware – artistic interpretation. Image credit: Alius Noreika, created with AI Image Creator

Cascade is designed for settings like smart traffic intersections, medical diagnostics, equipment servicing using augmented reality, digital agriculture, smart power grids and automatic product inspection during manufacturing – situations where AI models must react within a fraction of a second. It is already in use by College of Veterinary Medicine researchers monitoring cows for risk of mastitis.

With the rise of AI, many companies are eager to leverage new capabilities but worried about the associated computing costs and the risks of sharing private data with AI companies or sending sensitive information into the cloud – far-off servers accessed through the internet.

Also, today’s AI models are slow, limiting their use in settings where data must be transferred back and forth or the model is controlling an automated system.

A team led by Ken Birman, professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science, combined several innovations to address these concerns.

Birman partnered with Weijia Song, a senior research associate, to develop an edge computing system they named Cascade. Edge computing is an approach that places the computation and data storage closer to the sources of data, protecting sensitive information. Song’s “zero copy” edge computing design minimizes data movement.

The AI models don’t have to wait to fetch data when reacting to an event, which enables faster responses, the researchers said.

“Cascade enables users to put machine learning and data fusion really close to the edge of the internet, so artificially intelligent actions can occur instantly,” Birman said. “This contrasts with standard cloud computing approaches, where the frequent movement of data from machine to machine forces those same AIs to wait, resulting in long delays perceptible to the user.”

Cascade is giving impressive results, with most programs running two to 10 times faster than cloud-based applications, and some computer vision tasks speeding up by factors of 20 or more. Larger AI models see the most benefit.

Moreover, the approach is easy to use: “Cascade often requires no changes at all to the AI software,” Birman said.

Alicia Yang, a doctoral student in the field of computer science, was one of several student researchers in the effort. She developed Navigator, a memory manager and task scheduler for AI workflows that further boosts performance.

“Navigator really pays off when a number of applications need to share expensive hardware,” Yang said. “Compared to cloud-based approaches, Navigator accomplishes the same work in less time and uses the hardware far more efficiently.”

In CVM, Parminder Basran, associate research professor of medical oncology in the Department of Clinical Sciences, and Matthias Wieland, Ph.D. ’21, assistant professor in the Department of Population Medicine and Diagnostic Sciences, are using Cascade to monitor dairy cows for signs of increased mastitis – a common infection in the mammary gland that reduces milk production.

By imaging the udders of thousands of cows during each milking session and comparing the new photos to those from past milkings, an AI model running on Cascade identifies dry skin, open lesions, rough teat ends and other changes that may signal disease. If early symptoms are detected, cows could be subjected to a medicinal rinse at the milking station to potentially head off a full-blown infection.

Thiago Garrett, a visiting researcher from the University of Oslo, used Cascade to build a prototype “smart traffic intersection.”

His solution tracks crowded settings packed with people, cars, bicycles and other objects, anticipates possible collisions and warns of risks – within milliseconds after images are captured. When he ran the same AI model on a cloud computing infrastructure, it took seconds to sense possible accidents, far too late to sound a warning.

With the new open-source release, Birman’s group hopes other researchers will explore possible uses for Cascade, making AI applications more widely accessible.

“Our goal is to see it used,” Birman said. “Our Cornell effort is supported by the government and many companies. This open-source release will allow the public to benefit from what we created.”

Source: Cornell University

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radiance1 · 2 years

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I've been thinking about Timmy Turner lately and if what I've seen on the Omniverse Battlefield Wiki is true. (And things from VS Battle Wiki)

I'd say that Timmy is pretty fucking stacked if he ever ended up in the Dc universe.

Not that he would be invincible or whatever, I'm just saying he could put up a fight.

Well, that's if he has access to a lot of his stuff. Thought that isn't to say he's a slouch in the mental department if push came to shove.

By Himself (regularly):

Genius Intelligence (At best he's an excellent strategist, leader, manipulator, user of weapons, and with creator of technology)

Size Decreasing (Shrinky Suit, of himself and those around him)

Time Travel (Time Scooter, Re-Do Watch)

Time Manipulation (Re-Do Watch; Turns back time to specific points of it. Can also send him to previously lived futures that shouldn't be impossible to access due to the actions/conditions in the present)

Empathic Manipulation (Cupid's Bow and Arrows)

Weapon Mastery (skilled with Bow and arrows, A lasso, a shield, a magic mirror to aim and return attacks back at a foe, a sword, a bag/cape to cover himself with, explosive easter eggs, an improvised whip, etc)

Vehicular Mastery (Timmy's Vehicular Mastery - GIFs - Imgur)

Unexplored Chosen One powers (Incapacitated many Eliminators/robots by touching one of them, previously blew them up by throwing mundane objects at them, in both cases not knowing how he did it. At worst he was fulfilling his destiny to enlighten the Darkness and can't repeat these powers, at best he can always unconsciously incapacitate robots by touching them)

Status Effect Inducement (Toothbrush Bracelets)

Mind Manipulation (Floss Lasso of Truth)

Access to Fairy Magic (Magic Muffin)

Memory Erasure (Forget-Me-Knob)

Immersion

Age Manipulation (Magic Tv Remote)

Explosion Manipulation (Exploding Easter Eggs)

Flight (Magic Jetpack)

Self-Substance (Type 1 via magic disguise glasses)

Attack Reflection (Magic Mirror)

Duplication (Magic Copy Machine)

Fate Manipulation & Pain Manipulation (You Doo Dolls)

Possession (Body-swapping Joy Buzzer)

*Resistance to the powers Magic has in the verse (All of them, only applies to the items themselves)

Magic Wand (occasionally given)

Excalibur (Returns to him when thrown)

Geek-To-Girl translator

Auto Poofer

Sleeping Gas (and more equipment).

Extrasensory Perception (Recognized the alterations in time done by Vicky when everyone else was unaware of them)

Acasuality:

*Prevented the thing that made his parents meet, therefore making him not exist to which he still did.

*Was unaware of a change in the past that caused the internet's name to be exchanged with his own.

*The first future version of him shown could travel back to Timmy's present and prevent him from doing something inconvenient, and still exist

*Wished to have never been born, altering the timeline into one where his parents had a daughter instead of him and all the people he related to had a different life, but Timmy himself wasn't affected by this beyond momentarily having white clothes and becoming "nonexistent" only in the sense that he was never born; others could interact with him normally and he could interact with his surroundings.

Toon Force.

Acrobatics ((Some interpretable part of it should not come from his Toon Force)

Heat Vision (Wished for it once and kept the power)

There is like, so much more I can put here. But I'm putting them on a reblog post bruh.

#the fairly oddparents #Timmy Turner #crossovers #Dc #there's so much to do #but I can do it #probably #Also haven't watched Timmy Turner in a long while #so I'm gonna be relying on the Omniverse Wiki and the Vs Battle Wiki

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erkinsagiroglu · 2 years

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Artificial Intelligence: Fascinating Opportunities & Emerging Challenges with Professor Bart Selman

One of the reasons that this particular topic aroused my interest is that I am concerned with analytics and artificial intelligence area for the past couple of years and worked as a machine learning engineer. Although my company was more concerned with general industrial problems like predictive maintenance on the production line, predictive quality and such, the academia’s direction is always a leading one regarding key findings in the area that are later transformed into technologies which are used by these companies. This is why it is crucial to keep track of important researches and researchers in the field regularly. This is the main reason that the topic engaged my attention.

The sub-topics of the interview revolve around the breakthroughs and new findings of the AI and the possible capabilities of the future AI. While these subjects are common in most of the media and social media platforms, in this interview Professor Bart Selman gave me some particular insights for different topics. First of all I updated myself regarding the state of competition between the human and the AI. General AI, being an extremely difficult concept, that aims for a super model that can perform different tasks of today by itself at the same time. These tasks include computer vision, natural language processing and such. Prof. Selman states that it requires a concept of “understanding” for the model. For instance, unlike today’s translator models which are basically trained on hundreds of thousands of translations and act likewise, they must come to the point where they really understand the meaning of the sentence and Bart Selman states that he is optimistic about these innovations happening in the near future. What I also have learnt is the importance of explainable AI. Prof. Bart Selman states that these concepts have already being studied for a long time but as the breakthroughs happened in the field and AI has begun to having a decisive role regarding the critical matters in people’s daily lives like loans or hirings, societies have become more aware of the importance of the reasoning behind these decisions made by AI. Bart Selman states that there are some studies proceeding on determining whether the decisions made by AI are biased towards some factor (e.g. gender) or not. One of the most critical subjects that I have learnt from the interview is the concept of Artificial Reasoning as Professor Bart Selman explains the subject very clearly. My perception regarding the AI models and their potential capabilities was different before listening the interview. As I knew, AI models (except reinforcement learning) are trained on a dataset, they learn some deep patterns from the dataset that cannot be programmed by a human and learns only from that dataset. Artificial Reasoning on the other hand, is concerned with creating a model that can learn the logical reasoning. While Professor Bart Selman states that the researches have been proceeding yet, this is a whole another dimension for the capabilities of the artificial intelligence. Creating a model that can help to solve mathematical theorems, to find the solutions for some unanswered questions on physics or giving definite answers to some philosophical questions opens a new door both for the field and the industry.

The guest researcher, Prof. Bart Selman, is a faculty member of Cornell University’s CS department. He has contributed to more than 300 articles and being cited more than 30.000 times overall. In the interview he talks about his researches for Artificial Reasoning and how it has a potential to surpass the human level exponentially. Some of his other recent researches include Fairness for Cooperative Multi-Agent Learning with Equivariant Policies which he also talks about explainability in the interview. Artificial intelligence for materials discovery is another research that he contributed. In general he is more concerned with unique topics like reinforcement learning, optimization solvers and artificial reasoning more than he is concerned with some other popular subjects in the field like computer vision and natural language processing. He believes that these techniques can be used to widen the perspective for mathematicians and fundamental and natural scientists in order to discover and solve new concepts with the big contributions of AI.

#SoundCloud

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ejbarnes · 2 years

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Art Using Artificial Intelligence, and What It Means for Human Artists

DALL-E 2 is but one of several artificial-intelligence transformer models designed to create art (broadly defined) based on natural-language descriptions. According to a recent post on Jason Horej’s RedDot Blog, DALL-E 2’s “machine-learning system was ‘trained’ on a data set of 12 billion images” to produce new images based on natural language input.

Horej’s sensational headline of “AI is coming for your job” grabs your attention, but then he pivots: In the long run, AI could be added to the artist’s toolbox.

The potential revolution goes beyond Horej’s list of uses for brainstorming/thumbnailing, marketing, and the like. That’s because human-produced art has historically already had to react to a previous threat: Photography.

The rise of photographic technology displaced drawing and painting for a significant portion of art’s traditional purpose: Documenting real persons, places, and things. Consider how today, we compare painted portraits of Abraham Lincoln (or his engraved portrait on the $5 bill) with known contemporary photographs of him; how Mathew Brady’s gritty black-and-white photographs of Civil War battlefields helped dispel some of the mystique surrounding the meat grinder of modern warfare; and how Ansel Adams took landscape photography itself beyond documentation and into the realm of art.

In reaction to photography’s encroachment on fine art and illustration’s traditional territory, handmade art in the nineteenth and twentieth centuries was under pressure to do things that photography couldn’t (yet): Portray historical persons or events from before photography, render fantastical scenes, and most controversially at the time, use new drawing, painting, and printing techniques to push the envelope of everyday perception.

The explosion in new art styles and movements in the late 19th and early 20th centuries can be laid directly at the feet of photography’s challenges. Impressionism, pointillism, cubism, fauvism, surrealism, dada, expressionism, color field painting, pop art, and more – all were undertaken by their practitioners to make sure that mark-making remained a relevant endeavor.

I dare not speculate what directions fine artists and illustrators will take in order to stay a step ahead of AI’s capacity to produce painterly, fantastical, and even abstract images using textual descriptions to crib from the entire history of visual art.

I will, however, speculate on what the developing technology means for comics creation.

* * *

When I was first workshopping my comics art with fellow comic creators, I was in an APA, or Amateur Press Association – a multi-author zine. Ours was quite a hefty one, printed at 8.5” x 11” and often a quarter-inch thick or more, and as it was an APA for comics creators, our raison d’être was critiquing each other’s work. A couple of our members were comics letterers – the folks who add the dialog balloons, captions, and sound effects to comics art. In those days, comics lettering was almost always done by hand with a dip pen, along graphite guidelines ruled using an Ames guide (later produced by Alvin, who have themselves now been taken over by another company). Possibly the sole exception to comics hand-lettering was Mad Magazine, the text for which had to be typeset, printed out, cut up to fit the word balloons, and pasted onto the original art or photostat (a high-quality black-and-white copy made with a photographic machine, heavily used in print production departments before photocopies got good). This paste-up process most likely used the traditional paste-up tools of X-Acto knives and rubber cement, as it was the state of the art for decades.

Coloring of comics was different in those days, too. Four-color (CMYK) separation had to be done by hand, using three acetate overlays: One each for the transparent colors of cyan (C), magenta (M), and yellow (Y). The colorist would attach registration marks (pre-printed on clear plastic tape) to the corners of the original art beyond the print margins, and to each overlay, aligning them to make sure the printer correctly aligned the cyan, magenta, and yellow to the black when it came time to print.

For each overlay, the colorist would affix pieces of translucent Rubylith to correspond to solid color, and Zip-a-Tone or other mechanical screen tone to use regular patterns and sizes of dots to imitate color densities less than 100%. For all the labor involved, hand separation was a blunt instrument; if you wanted to take advantage of a wide range of colors, you needed a color guide book (see photo). For speed and a standardized house look, especially on series, most comics colorists were expected to stick to a limited palette, relying on the inker’s solid black (the K in CMYK) for shadows. Unless you had special graduated screen tone sheets, gradients were simply impossible. If you tilted your tone screens wrong relative to each other, a Moiré effect could result.

By the late 1990s, both lettering and coloring for comics had gone digital. As a result, while the comics letterer went from being an artist to being a graphic designer, the colorist went from being a graphic designer to being an artist. All sorts of special effects became possible – and, most interesting to me in my own work, digital printing automated the color separation process, allowing comics to be published using traditional art media including watercolor, collage, acrylics, and gouache.

* * *

What will natural-language-driven AI art mean for the future of comics? Will every comics writer be able to illustrate their own comics without having to partner with an artist? Will writer-artists become simply...writers?

It will probably be a lot more complicated than that. Consider how digital lettering is not just typing; there are still design skills involved, some of them similar to the skills hand-letterers used (and still use).

The writer describing the scene will still have to specify whether a character is on the left or right side of the panel, whether there’s action both in the foreground and the background, the scenery, the color palette, lighting issues – the writer will, in fact, have to specify in words things that an artist might decide for themselves based on their judgment of what they think the writer wants. And the writer will have to do this for every panel – just as they’d have to write a panel description for every panel for an artist, only they wouldn’t be able to rely on the artist’s judgment to solve some of the visual problems. For example, if they are writing a super-hero story with a fight scene, the writer will have to choreograph the action in detail, panel by panel.

AI is not going to take over fine art; as Horejs points out, there will always be customers for whom having an original piece – that is, a unique physical artifact made by human hands – is important. For nearly 200 years – going back to the days of Currier and Ives – color prints have reached an audience that could never afford original art. Digital prints constructed using artificial intelligence based on natural-language input are unlikely to shift the art market significantly. What will be different is how easily those print customers will get the kind of image they want; and there, the results will only be as good as the description. As we used to say in the computer biz, garbage in, garbage out.

#artificial intelligence #AI and art #comics #APAs #lettering #printing #print production #original art

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interest-articles · 2 months

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Professor Terrence Sejnowski Receives The Brain Prize for Advancements in Computational Neuroscience

Professor Sejnowski's Contributions to Understanding Brain Function and Artificial Intelligence Recognized

Professor Terrence Sejnowski, a distinguished professor in the UC San Diego Department of Neurobiology and head of Salk's Computational Neurobiology Laboratory, has been awarded The Brain Prize for his groundbreaking work in computational neuroscience. The Brain Prize, the world's largest neuroscience research prize, recognizes individuals who have made highly original and influential advances in brain research. Professor Sejnowski's contributions have not only deepened our understanding of brain function but have also paved the way for advancements in artificial intelligence.

Professor Richard Morris, chair of The Brain Prize Selection Committee, emphasizes the significance of computational and theoretical neuroscience in modern brain sciences. He commends Professor Sejnowski and his fellow prize winners for their novel approaches and conceptual frameworks that have revolutionized the field. Their work has provided crucial insights into fundamental brain processes, such as learning, memory, perception, and the mapping of the external world.

Moreover, their research has shed light on neurological disorders and inspired the development of brain-inspired artificial intelligence.

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The Boltzmann Machine and Learning in Neural Networks

One of Professor Sejnowski's most significant contributions came in 1985 when he collaborated with computer scientist Geoffrey Hinton to invent the Boltzmann machine. This algorithm was the first to solve the problem of learning in multilayered neural networks. Its biological plausibility set the stage for subsequent learning algorithms in artificial neural networks.

The Boltzmann machine remains a milestone achievement, bridging the gap between computer science and neuroscience.

NETtalk and the Intersection of Engineering and Cognitive Science

In addition to the Boltzmann machine, Professor Sejnowski created NETtalk, a groundbreaking computer program that learned to convert written text into speech. This achievement not only showcased impressive engineering capabilities but also posed new challenges for philosophy, linguistics, and cognitive science. NETtalk's ability to mimic the human brain's language processing capabilities marked a significant cultural milestone and sparked interdisciplinary discussions.

Advancements in Brain Imaging and Sleep Research

Professor Sejnowski's contributions extend beyond learning algorithms and language processing. He played a pivotal role in developing the first unsupervised learning algorithm for independent component analysis, a technique widely used in brain imaging. His research also challenged previous assumptions about sleep spindles, revealing that these brain wave patterns during nonrapid eye movement sleep create circular traveling waves rather than synchronous activity across the cortex.

These findings have expanded our understanding of sleep and its impact on brain function.

Recognition and Impact

Professor Sejnowski's remarkable achievements have garnered numerous accolades and awards. He was named the 2024 Scientist of the Year by the ARCS Foundation of San Diego and received the Gruber Prize in Neuroscience, the Institute of Electrical and Electronics Engineers Frank Rosenblatt Award, Neural Network Pioneer Award, Hebb Prize, and Wright Prize. His membership in prestigious academies, including the National Academy of Sciences, National Academy of Medicine, National Academy of Engineering, and National Academy of Inventors, further exemplifies his impact on the scientific community.

Professor Terrence Sejnowski's receipt of The Brain Prize highlights his exceptional contributions to computational neuroscience. His pioneering work in the development of the Boltzmann machine, NETtalk, and independent component analysis algorithms has revolutionized our understanding of brain function and shaped the field of artificial intelligence. By unraveling the complexities of learning, memory, perception, and sleep, Professor Sejnowski has paved the way for advancements in brain-inspired technologies and provided crucial insights into neurological disorders.

The recognition of his scientific achievements underscores the importance of interdisciplinary collaborations and the potential for computational approaches to transform our understanding of the brain.

#all

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onlinemarketingbangalore · 4 months

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Unlocking Sales Excellence: The Impact of Automation on Modern Sales Processes

In the ever- evolving geography of business, learning deals is more critical than ever. Enter the realm of slice- edge top CRM software and advanced lead operation systems, reshaping how businesses navigate their deals trials. This comprehensive disquisition delves into the transformative part of robotization, unraveling how it influences supereminent operation, client relations, and eventually, profit generation.

employing the Power of Top CRM Software Supercharging Efficiency and Productivity At the heart of contemporary deals strategies lies the game- changing top CRM software. Armed with intelligent robotization features, it empowers deals brigades to optimize effectiveness and productivity. Mundane tasks like data entry, contact operation, and follow- ups seamlessly transition into automated processes, allowing deals representatives to concentrate on erecting genuine connections with implicit guests.

Casting acclimatized client peregrinations The hallmark of exercising top CRM software is the capability to draft individualized client peregrinations. robotization facilitates precise followership segmentation grounded on different criteria, enabling targeted communication. This substantiated approach not only elevates the client experience but also significantly enhances the liability of converting leads into pious, long- term guests.

learning the Dynamics of Lead Management Systems Streamlining the Lead Acquisition Journey At the core of a successful deals channel lies a robust lead operation system that goes beyond introductory lead shadowing. Through robotization, the entire lead accession process becomes streamlined – from landing leads across colorful channels to assigning them to the right deals representatives. The result is an effective system that ensures no implicit occasion slips through the cracks.

Precision in Nurturing Leads robotization within supereminent operation extends to precise lead nurturing – a critical hand of the deals process. Through automated drip juggernauts, businesses can deliver targeted content at every stage of the buyer's trip. This strategic nurturing not only maintains supereminent engagement but also positions the brand as a trusted authority in the assiduity.

Integration for Seamless Operations Achieving Synergy through Automated Integration To truly optimize deals processes, businesses are decreasingly espousing intertwined results. The flawless integration of top CRM software with other essential business tools, similar as dispatch marketing platforms and analytics tools, creates a unified ecosystem. This community ensures the flawless inflow of data across different departments, furnishing a holistic view of client relations and enhancing decision- timber.

Real- time Analytics for Informed Decision- Making robotization not only streamlines processes but also provides inestimable perceptivity through real- time analytics. By employing the power of data, businesses can make informed opinions, identify trends, and proactively address challenges. The integration of analytics within the CRM system equips deals brigades with the knowledge demanded to acclimatize strategies and stay ahead of request dynamics.

The Future of Automated Deals Processes Embracing Innovation for a Competitive Edge As technology advances, the part of robotization in deals processes is set to evolve indeed further. Artificial intelligence and machine literacy will play a more significant part in prophetic analytics, allowing businesses to anticipate client requirements. Embracing these inventions is pivotal for maintaining a competitive edge in the dynamic business geography.

conforming to Shifting Consumer geste robotization not only enhances internal processes but also aligns businesses with changing consumer geste . As guests decreasingly seek substantiated gests , automated deals processes enable businesses to efficiently meet these prospects. The capability to acclimatize to evolving consumer trends positions companies as leaders in the request.

Conclusion In conclusion, the integration of top CRM software and advanced lead operation systems represents a paradigm shift in how businesses approach deals. robotization, with its capability to enhance effectiveness, epitomize relations, and give practicable perceptivity, is the linchpin. Thriving in the competitive request requires using these technologies to streamline deals processes and cultivate enduring client connections.

#best crm management software #crm for startups #popular crm software #top crm software

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managerteams · 10 months

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Unveiling the Ethereal Realm: The Rise of Ghost Talking Apps

Introduction:

In a world where technology and the supernatural collide, the concept of communicating with spirits may seem like something out of a sci-fi movie. However, with the advent of ghost talking apps, bridging the gap between the living and the deceased has become a tangible reality. This article explores the fascinating realm of ghost talking apps and their impact on our perception of the afterlife.

The Fascination with the Paranormal:

From ancient folklore to modern-day horror movies, the concept of ghosts and spirits has intrigued humans for centuries. We have always wondered about the existence of an afterlife and longed to communicate with those who have passed away. Ghost talking apps, leveraging the power of technology, have tapped into this fascination, offering a new means to connect with the spiritual realm.

The Evolution of Ghost Talking Apps:

Initially, ghost talking apps were limited to basic features, such as generating random words or sounds thought to be associated with spirits. However, as technology advanced, so did these applications. Today, ghost talking apps employ sophisticated algorithms, utilizing voice recognition and machine learning to interpret and respond to user inputs. These apps enable users to ask questions and receive direct responses, as if engaging in a conversation with the deceased.

Unraveling the Mechanics :

Ghost talking apps utilize a variety of methods to establish communication. Some apps employ the Electronic Voice Phenomenon (EVP), where voices from the spiritual realm are captured and processed electronically. Others utilize intelligent algorithms to generate coherent responses based on user input. While skeptics argue that these apps rely on chance or suggestion, many users claim to have experienced profound and personal interactions with departed loved ones, leading to debates around the nature of consciousness and the existence of an afterlife.

Controversies and Ethical Considerations :

The rise of ghost talking apps has also sparked controversies. Skeptics argue that these apps prey on vulnerable individuals seeking closure or comfort, potentially exploiting their grief. Furthermore, the ethical implications of attempting to communicate with the deceased remain a topic of heated debate. Critics caution against placing blind faith in technology and emphasize the importance of maintaining a critical perspective when using these apps.

Conclusion:

Ghost talking apps have undeniably opened new avenues for exploring the supernatural and engaging with the afterlife. Whether viewed as mere entertainment or genuine tools for connecting with departed spirits, these applications have captivated the imagination of millions. While the debate surrounding their authenticity continues, one thing is certain: ghost talking apps have revolutionized our perception of life and death, prompting us to ponder the mysteries that lie beyond the veil of existence.

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ghost talking app

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matlabassignmenthelp-blog · 2 years

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What It Artificial Intelligence & How It Is Used

What Is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is the imitation that human-like intelligence in machines programmed to act as humans do and to mimic their behavior. It can also be used to describe any machine with characteristics that are similar to human brains such as problem-solving and learning.

The primary quality for artificial intelligence lies in its capacity to think rationally and take decisions which have the highest chance of reaching a particular purpose. One subset in artificial intelligence includes machine learning (ML) that is the notion that computer programs automatically learn , and then adapt themselves to the new data , without the assistance of humans. Deep learning techniques allow for automatic learning by the absorption of massive quantities of unstructured data, such as images, text or videos.

Note: If you are a student and enhnace you knowledge of the Artificial Intelligence, then you can get help from our experts Artificial Intelligence Assignment Help.

KEY TAKEAWAYS

Artificial Intelligence (AI) is the replication or approximation to human cognitive abilities in machines.

The objectives of artificial intelligence include computer-enhanced learning, thinking and perception.

AI is used in a variety of industries, from healthcare to finance.

The weak AI is typically focused on a single task however, strong AI takes on with tasks that are more complicated and human-like.

Certain critics worry that the widespread use of the latest AI could affect negatively society.

Understanding Artificial Intelligence (AI)

When people hear the word artificial intelligence the first thing that they imagine is robots. This is because films with big budgets and novels tell stories of robotic machines that cause chaos on Earth. Nothing could be more far from the truth.

Artificial intelligence is founded on the idea that human intelligence is defined in the manner that machines could quickly mimic it and complete tasks, ranging from the most basic to those that are more complicated. The objectives of artificial intelligence include mimicking human cognitive activities. Researchers and researchers in this field have made astonishingly rapid advancements in mimicking processes like reasoning, learning and perception, so that they are able to be defined. Many believe that the next generation of innovators will soon be able to create systems that surpass the ability of human beings to learn or think about every subject. Others remain skeptical, as every cognitive process is interspersed with value judgements that are influenced by human experiences.

Applications of Artificial Intelligence

The applications of artificial intelligence are limitless. AI is applicable to different industries and sectors. AI is currently being evaluated and utilized in the medical industry to dosing medications and pouring out various treatments specifically that are specific to patients and also to assist in surgery operations in an operating theatre.

Some other examples of computers equipped with artificial intelligence are computer systems that can play games like chess, and self-driving vehicles. All of these machines have to consider the implications of every move they make as every move will affect the final outcome. In chess the final result is that you win the game. Autonomous vehicles' computer system has to take into account any external data and calculate it to move in the way that avoids the possibility of collision.

Artificial Intelligence also has applications in the financial sector which is where it's used to identify and flag up suspicious activity in financial and banking sectors like irregular debit card use and massive account deposits, all that aid banks' fraud department. Applications of AI are also being utilized to streamline and facilitate trading. This is achieved by making demand, supply and pricing of securities more easy to determine.

Types of Artificial Intelligence

Artificial intelligence is divided into two distinct categories: strong and weak. The weak AI is an algorithm specifically designed to do a specific job. The weak AI systems are those that play video games like the chess game from above, as well as personal assistants, such as the Amazon's Alexa as well as Apple's Siri. The assistant is asked for a query and it will answer it for you.

Artificial intelligence systems that are strong are those that can perform the tasks that are thought to be human-like. They tend to be more complex and intricate systems. They are designed to deal with situations in which they are needed to solve problems without the intervention of a human. Such systems are located in applications like self-driving automobiles or in operating rooms in hospitals.

Special Considerations

Since its inception the concept of artificial intelligence has been criticized by researchers and public alike. A common issue is that machines will be advanced enough that humans won't have the ability to keep pace and will be able to take off by themselves, re-inventing themselves in an exponential manner.

Another reason is that machines could infiltrate privacy and can even be used as weapons. Others debate the morality of artificial intelligence, and whether intelligent systems like robots are entitled to the same rights as human beings.

Self-driving vehicles have been controversial because they tend to be designed to have the least risk possible and the smallest number of injuries. If faced with the possibility of collision with one person or another in the same space the cars will calculate the best option to cause the minimum amount of harm.

What Are the 4 Types of AI?

Artificial intelligence can be classified into four different types.

Reactive AI utilizes algorithms to improve outputs based on inputs. Chess-playing AIs, as an example are systems that react to find the most efficient strategy to win. Reactive AI is typically relatively static, and is unable to change or adapt to changing circumstances. This means that it will generate the same output when given identical inputs.

The AI with limited memory can adjust to past experiences or modify itself on the basis of new observations or information. Most of the time, the frequency of updates is restricted (hence its name) and the length of memory is comparatively small. Autonomous vehicles, for instance can "read the road" and respond to new circumstances or "learning" from past experience.

Theory-of-mind AI are fully-adaptive and possess the ability to acquire and remember the past experience. These kinds of AI comprise advanced chat-bots which can be able to pass an exam called the Turing Test, fooling a person into thinking that it was actually a human. Although they are impressive and sophisticated they aren't self-aware.

Self-aware AIs, as the name implies, becomes sentient and conscious of their own existence. Yet, in the world of science fiction there are some who believe an AI is not aware and "alive".

#Artificial Intelligence #uses of Artificial Intelligence

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exelahrsolutions · 2 years

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2023 will welcome redirected focus on traceable real-time performance through HCM/HRMS. So, let's get you acquainted with these HR service and Payroll processing trends.

#ExelaHRSolutions #HRServices #HR #PayrollOutsourcingService #GlobalPayrollProcessing #RecruitmentProcessOutsourcing #HRTech #HROutsourcing #Payroll #PayrollServices #HumanResources #PayrollOutsourcing #PayrollProcessing #HRSolutions

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jayco-cio-services · 2 years

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Misled or Misinformed: How Business Owners Stunt Their Growth By Listening to Insecure Employees

When you're a leader, you rely on your team members to tell you the truth, So that you can make thoughtful decisions and feel confident that you know what's happening. Most repay your trust with truthfulness. But sometimes, you're faced with an employee who bends the truth too far or lies to you outright. When this happens, it is one of the most challenging managerial situations to meet because it's hard to be sure what's happening or tell yourself that you must be mistaken. I have said for years that CEOs of companies are only as smart as those around them. I still believe this, and I know CEOs are brilliant. However, a company can often have slow or stifled growth because the CEO listened to their employees who were afraid of change for many reasons. We all want to believe that employees are great. As intelligent managers, we think we can spot deceptive behaviors in an interview and background checks. We tell ourselves we have hired excellent and honest workers. Unfortunately, employees sometimes lie or embellish their background and qualifications. Several times, I have seen individuals exaggerate their credentials to negotiate a more prestigious position. Exaggerating to get a job creates a destructive dynamic as they are now the expert and are relied on for this information. In addition, most companies have scaled back staff by reducing costs year after year to meet financial goals, resulting in outsourcing IT departments or running internally on a skeleton crew and having staff resource issues to accomplish new and innovative projects. Still, rarely are employees incompetent; usually, they lack the skills and understanding for the job. Here are Some Reasons Why Employees can Mislead or Misinform You. - They lack the training or knowledge to keep up with new technologies or changes in best practices for your industry. - They lack the understanding of the CEO's goals and how they apply to their department. - They lack the experience to seek out what they don't know. - They are overly burdened with their current workload and lack the motivation to take on more. Being in the IT Industry for over 25 years, change has been all that I have experienced. I started programming in machine language (strictly 1's and 0's) and COBOL, worked on the first PCs and Mainframes, and even saw large companies through the Y2K crisis. There has been lots of change, and I have been excited about each new change as I have learned more and more about it. I also know the perception of "Consultants" that we are bad people only looking to break up employees and create chaos in companies. People hear the word and instantly think someone is trying to replace them. In today's world, unless companies are actively sending their IT staff for training several times a year, there is no way for them to keep up with the ever-changing skills needed in the IT industry. The only way for a CEO to fulfill their visions is to hire consultants to help with long- and short-term projects, especially in a technical arena. Here are some reasons why: - They are consultants for a reason. They are not looking to work for you as an employee; they don't want anyone's job. - They will have experience in a wide range of technology from different companies and industries and keep up with new and emerging trends. - They will have an extensive network of providers they can call on to help clients with projects and fill gaps in knowledge. JAYCO CIO Services As consultants, our mission is to educate, mentor, and help move our clients forward. We believe that people are good at their jobs, and when they fall short, it is usually because of a lack of experience or knowledge. We can help clients with career path training plans and strategic road maps to incorporate new technologies that can help streamline your company. With our flexible engagement arrangements, there is no long-term commitment. Because we believe you should only pay for what you need, so whether you need someone for a few hours a week or on a project basis, we can help you right now. At JAYCO CIO Services, we don't do anything besides CIO services. Right now, we are offering 50% off our CIO Assessment. The assessment is an excellent way to get to know us. We will work with your executive officers, stakeholders, and IT team to show you where you are deficient and supply you with a report to increase your understanding of where you need help. Read the full article

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360digitmg-training · 2 years

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Data Science Certification Coaching Course In Hyderabad

And if these instrument operations have obligatory tasks to finish, that’s indeed better. You can begin to construct your portfolio of data wisdom tasks before ever touching a job. Learn this instigative department of Artificial Intelligence with a program featuring 58 hrs of Applied Learning, interactive labs, 4 hands- on enterprise, and mentoring. With our Machine Learning instrument training, master Machine Learning generalities needed for a Machine studying instrument. This Machine Learning on- line coaching will give you the best demand to become a successful Machine Learning mastermind right now.

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This module will give you a deep understanding of exploring data sets exercising Pandas. Pandas Pandas can also be one of the considerably used Python libraries. NumPy This module will give you a deep understanding of exploring data units exercising NumPy.

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As part of this module, find out about one other Deep literacy algorithm SVM which is also a black box fashion. SVM is about creating boundaries for classifying data in multidimensional spaces. These boundaries are pertained to as hyperplanes which may be direct or non-linear boundaries which insulate the classes to the most margin possible. Learn about kernel tips mileage to convert the data into high dimensional areas to categorise the non-linear spaces into linearly divisible knowledge. The Boosting algorithms AdaBoost and Extreme Gradient Boosting are mentioned as part of this durability module You may indeed study mounding strategies.

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The program may be veritably nicely structured and a super combination of proposition and hands- on practice. “ Thanks to the DSE program at 360DigiTMG, I got 2 job offers, one from DXC Technology and one other from Razorthink. This program is a perfect blend of both star and hands- on operations. Taking this course to upskill myself was top- of- the- line opinions I ’ve made. Learn from main academicians within the area of Data Science and Engineering and colourful other educated assiduity interpreters from top organisations. Text bracket, Document vectors, Text bracket using Doc2vec In this module, you will be tutored much more about Text Bracket and Document Vectors using Doc2vec.

The coaches of the Data Science course are the assistant's main specialists who have 15 times of experience. They hail from transnational companies like Microsoft, Google, L&T, Cognizant, etc. The coaches listed under are the backbone of the Data Science training sect. Any graduate or postgraduate who is keen about making machines as people exercising logical and logical chops can be the stylish seeker for the Data Science coaching. colourful purposes like Iphone Siri, Amazon Alexa, Google Hunt, Mobile Games, Uber and Facebook are exercising operations of Data Science and hence the demand. The complexity between inordinate demand and give holes is contributing to grim stalking for Data Scientists because the provision is at bare minimum.

The PG Data Science course is permissible for campaigners in their ultimate semester and contemporary graduates with 0- 3 times of experience. campaigners should retain a combination of 60 or over in Xth, XIIth, and Maids. A force letter will be rolled out to choose many campaigners.

For more information

360DigiTMG - Data Analytics, Data Science Course Training Hyderabad

Address - 2-56/2/19, 3rd floor,, Vijaya towers, near Meridian school,, Ayyappa Society Rd, Madhapur,, Hyderabad, Telangana 500081

099899 94319

https://g.page/Best-Data-Science

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swarnalata31techiio · 2 years

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About Artificial Intelligence

Artificial intelligence (AI) is a huge-ranging department of computer technological know-how worried with constructing smart machines capable of completing tasks that commonly require human intelligence.

About Machine Learning

Machine learning (ML)is a branch of Artificial Intelligence (AI) and computer science which focuses on the use of facts and algorithms to imitate the way that humans study, regularly enhancing its accuracy. Difference between AI and Machine LearningArtificial Intelligence (AI) and Machine Learning (ML) are two very available words at this time, and often seem to be used interchangeably. They are not quite the same thing, but the perception that they are can sometimes lead to some confusion.So I write some piece of the word for different that. Both terms crop up very frequently when the topic is Big Data, analytics, and the broader waves of technological change which are sweeping through our world.In short, the best answer is that: Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”. And, Machine Learning is a current application of AI-based around the idea that we should just be able to give machines access to data and let them learn for themselves.

Artificial Intelligence

Artificial Intelligence is a technology that enables a machine to simulate human behavior.

The goal of AI is to make a smart computer system like humans to solve complex problems.

In AI, we make intelligent systems to perform any task like a human.

Machine learning and deep learning are the two main subsets of AI.

AI has a very wide range of scope.

AI is working to create an intelligent system that can perform various complex tasks.

Machine Learning

Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.

The goal of ML is to allow machines to learn from data so that they can give accurate output.

In ML, we teach machines with data to perform a particular task and give an accurate result.

Deep learning is the main subset of machine learning.

Machine learning has a limited scope.

Machine learning is working to create machines that can perform only those specific tasks for which they are trained.

#artificial #machine #technology #webdevelopment #techiio

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