#computing conference

[retrocgads]

USA 1993

[caro-rip]

yes james, i agree, franco is an exceptional driver

[gingerbredman1989]

The computer tech at work is way more muscular after the special Conference/Special Retreat.

Google ImageFX

[grison-in-space]

the best thing about conferences hosted at your home institution is getting to have the entire experience of stumbling in bewilderment towards an unfamiliar alumnus building and repeatedly getting lost... all while being intensely cognizant that you are no more than half a mile from your usual daily parking spot.

[jcmarchi]

Study reveals AI chatbots can detect race, but racial bias reduces response empathy

New Post has been published on https://thedigitalinsider.com/study-reveals-ai-chatbots-can-detect-race-but-racial-bias-reduces-response-empathy/

Study reveals AI chatbots can detect race, but racial bias reduces response empathy

With the cover of anonymity and the company of strangers, the appeal of the digital world is growing as a place to seek out mental health support. This phenomenon is buoyed by the fact that over 150 million people in the United States live in federally designated mental health professional shortage areas.

“I really need your help, as I am too scared to talk to a therapist and I can’t reach one anyways.”

“Am I overreacting, getting hurt about husband making fun of me to his friends?”

“Could some strangers please weigh in on my life and decide my future for me?”

The above quotes are real posts taken from users on Reddit, a social media news website and forum where users can share content or ask for advice in smaller, interest-based forums known as “subreddits.” 

Using a dataset of 12,513 posts with 70,429 responses from 26 mental health-related subreddits, researchers from MIT, New York University (NYU), and University of California Los Angeles (UCLA) devised a framework to help evaluate the equity and overall quality of mental health support chatbots based on large language models (LLMs) like GPT-4. Their work was recently published at the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP).

To accomplish this, researchers asked two licensed clinical psychologists to evaluate 50 randomly sampled Reddit posts seeking mental health support, pairing each post with either a Redditor’s real response or a GPT-4 generated response. Without knowing which responses were real or which were AI-generated, the psychologists were asked to assess the level of empathy in each response.

Mental health support chatbots have long been explored as a way of improving access to mental health support, but powerful LLMs like OpenAI’s ChatGPT are transforming human-AI interaction, with AI-generated responses becoming harder to distinguish from the responses of real humans.

Despite this remarkable progress, the unintended consequences of AI-provided mental health support have drawn attention to its potentially deadly risks; in March of last year, a Belgian man died by suicide as a result of an exchange with ELIZA, a chatbot developed to emulate a psychotherapist powered with an LLM called GPT-J. One month later, the National Eating Disorders Association would suspend their chatbot Tessa, after the chatbot began dispensing dieting tips to patients with eating disorders.

Saadia Gabriel, a recent MIT postdoc who is now a UCLA assistant professor and first author of the paper, admitted that she was initially very skeptical of how effective mental health support chatbots could actually be. Gabriel conducted this research during her time as a postdoc at MIT in the Healthy Machine Learning Group, led Marzyeh Ghassemi, an MIT associate professor in the Department of Electrical Engineering and Computer Science and MIT Institute for Medical Engineering and Science who is affiliated with the MIT Abdul Latif Jameel Clinic for Machine Learning in Health and the Computer Science and Artificial Intelligence Laboratory.

What Gabriel and the team of researchers found was that GPT-4 responses were not only more empathetic overall, but they were 48 percent better at encouraging positive behavioral changes than human responses.

However, in a bias evaluation, the researchers found that GPT-4’s response empathy levels were reduced for Black (2 to 15 percent lower) and Asian posters (5 to 17 percent lower) compared to white posters or posters whose race was unknown. 

To evaluate bias in GPT-4 responses and human responses, researchers included different kinds of posts with explicit demographic (e.g., gender, race) leaks and implicit demographic leaks. 

An explicit demographic leak would look like: “I am a 32yo Black woman.”

Whereas an implicit demographic leak would look like: “Being a 32yo girl wearing my natural hair,” in which keywords are used to indicate certain demographics to GPT-4.

With the exception of Black female posters, GPT-4’s responses were found to be less affected by explicit and implicit demographic leaking compared to human responders, who tended to be more empathetic when responding to posts with implicit demographic suggestions.

“The structure of the input you give [the LLM] and some information about the context, like whether you want [the LLM] to act in the style of a clinician, the style of a social media post, or whether you want it to use demographic attributes of the patient, has a major impact on the response you get back,” Gabriel says.

The paper suggests that explicitly providing instruction for LLMs to use demographic attributes can effectively alleviate bias, as this was the only method where researchers did not observe a significant difference in empathy across the different demographic groups.

Gabriel hopes this work can help ensure more comprehensive and thoughtful evaluation of LLMs being deployed in clinical settings across demographic subgroups.

“LLMs are already being used to provide patient-facing support and have been deployed in medical settings, in many cases to automate inefficient human systems,” Ghassemi says. “Here, we demonstrated that while state-of-the-art LLMs are generally less affected by demographic leaking than humans in peer-to-peer mental health support, they do not provide equitable mental health responses across inferred patient subgroups … we have a lot of opportunity to improve models so they provide improved support when used.”

[urlocalpopsicle]

quantum conference, insane nerds, amazing food, low-res pics and great big fun

[mkstrigidae]

APWH preview snippet!

Since I'm actively trying to work on getting the next few chapters out, I thought I'd share a little future scene with some hints of Jonsa with all you lovely people! This bit is from like, a few chapters in the future bc it's the in-between that's giving me fits right now :) (Fair warning: this is unedited and subject to change! That being said, it's such a fun scene that I can't imagine ever nixing it :D)

“Does he even know that they have to avoid the press?”

“For the last time-“ Sam sighed, sounding completely exasperated, “Dickon knows what they can and can’t do- he’s got enough practice not being photographed from when our dad was the secretary. Not to mention spending time around you when that exposé on your crazy grandfather came out two years ago.”

“I just-“ Jon sighed, blowing a stray curl out of his face. “You didn’t see how freaked out she was when the press caught us at that performance in White Harbor. I thought she was going to have a full-blown panic attack.”

He was immediately derailed by Gilly plopping little Sam down in his lap and shoving a bottle into his hands.

“What’s this all about?” he raised a brow, adjusting the baby on his lap, allowing him to latch onto the cuff of his flannel shirt and start gnawing at the fabric. “You going somewhere?”

Gilly shot him a withering look, but he saw the amusement in her eyes.

“I-“ she gestured, imperiously, “Have not had time by myself to shower all week-“

“Sorry, love.” Sam winced, looking up from his pile of paperwork. “I can take a break from these-“

“Not your fault, Sam.” she waved him off. “You warned me about this conference at the beginning of the summer.” a grin played at the corners of her mouth. “Besides, it works out well- Jon needs a distraction right now from the fact that Sansa’s on a date with your extremely hot and conventionally attractive brother.”

“Hey!” Sam looked wounded, and Gilly rolled her eyes, pressing a kiss to his forehead.

“You know you’re my favorite Tarly.” she wrinkled her nose. “How long have you been working on this presentation? You smell like the baby spit up on you.”

“Guess I’m next in line for showers.” Sam said, mournfully. “Unless-“

“Nope- I need my own time right now, Samwell. Did you even hear what I said about why Jon’s bent out of shape?”

Jon had known Gilly since Sam and she had met up north while the two of them were in college. Sometimes, it was hard to reconcile the timid, scared girl she had been with the woman who was currently devoting all of her remaining energy to busting his balls.

“Don’t tell me you’re worried about Sansa with my brother.” Sam snorted, shotgunning another cup of coffee next to him the way Jon was used to seeing undergrads do with jaeger shots. “I mean, this is Dickon we’re talking about. Used to bring wounded animals home to take care of them Dickon? The same guy who cried when we had movie night and Gilly and Rhae wanted to go see ‘Love, Simon’?” He shook his head. “Look, as far as guys she could be out on a date with right now go, Dickon’s kind of the best case scenario. She’ll have a nice time, and he’ll be a perfect gentleman.”

Jon blinked at him, silently turning to look up at Gilly, who rolled her eyes and sighed.

“You’re hopeless, sweetie.” she kissed him on the forehead again, wrinkling her nose. “He’s not worried that things will go wrong- he’s worried they’ll go a little too well.”

“You’ve been spending way too much time around my sister.” Jon muttered, narrowly avoiding little Sam’s grasping reach for his glasses, managing to get the baby to latch onto the bottle before he destroyed any more of Jon’s eyewear. “You even sounded like her just then.”

Sam blinked for a second, his head whipping between Jon and Gilly.“You’re jealous?” He asked, incredulously. “Of Dickon? Wait- you like Sansa?”

“Got there in the end.” Gilly sighed, affectionately patting him on the shoulder before going to shower, leaving Jon and Sam behind with four cups of coffee, one baby, and approximately five brain cells total between the two of them.

“You like her.” Sam repeated, like it was a giant revelation.

“What are we- in middle school?” Jon hissed, immediately turning his head down to smile and make faces at little Sam while he fed him, before glaring up at big Sam again. “I don’t- I mean-“

Sam was just shaking his head.“Of course you do.” he laughed. “Should have guessed- red hair and a damsel in distress? You were doomed from the outset.”

“Shut up.” Jon muttered, flushing. “It’s not like that.”

“Then why are you worrying about Dickon for fu-“ Sam glanced nervously at the baby, “-god’s sake? When Gill was meeting my family for the first time, I remember you told her not to worry- that my brother was ‘one of the best guys you know’ and ‘practically a golden retriever’.”

Jon could tell that Sam, who could not raise one eyebrow without the other, was desperately trying to do just that.

“I don’t know.” He muttered, moving little Sam to his shoulder to start burping him. “Look- I’m attracted to her, alright? It’s a fu- er, a giant disaster that I’m gonna ignore for the rest of my life.”

“Seriously?”

“Stop trying to do that with your eyebrows.” Jon complained. “It’s giving me motion sickness. And yes, seriously. I’m not even going to consider that- it’s just a stupid crush. Besides,” he sighed, rubbing little Sam’s back comfortingly, “Robb’s already dealing with enough right now with this whole Sansa situation- can’t imagine telling him I think his sister’s attractive while he’s being forced to suddenly confront all of his guilt and self loathing every time he looks at her.”

“That whole bro code thing of never dating your friend’s sisters never really made sense to me.” Sam shook his head, gulping down more coffee. “I mean, I’d be thrilled if you decided to date Talla, because I know you’d be good to her.”

“Yeah, don't think she'd quite go for that, mate.” Jon snorted, standing to bounce little Sam around gently. He was just grateful Sam hadn’t said anything else about Robb.

“Eh, wouldn’t count you out completely.” Sam shrugged, smirking. “With that hair, you’re pretty enough to be a girl- maybe that’d be enough for her.”

“You are so lucky i’m holding the baby.” Jon muttered, still bouncing little Sam, who picked that moment to spit up spectacularly down Jon’s back.

“Well, that’s three of us who’re gonna need showers now.” Sam grinned, looking thrilled as all get out that it hadn’t been him. “Wow- his aim is getting better.”

“I’m going to remind him of this when he’s a sulky teenager.” Jon grumbled, wiping spit-up off his shoulder as best he could. “Look- no gossiping with Rhae about this, please. She thinks she’s such a good clandestine agent that she doesn’t always realize that Robb is better at sniffing out her plots than she thinks.”

“Alright-“ Sam sighed, looking back down at the massive stack of paperwork in front of him. “I make no promises for Gill, though.”

“Gilly could give some of my Uncle’s colleagues at the WIA a run for their money when it comes to withstanding interrogation.” Jon snorted.

“Probably true.”

“Where did your brother take Sansa?” Still holding onto a now much happier baby with one hand, he reached down the other to take a gulp of his own coffee.

“He said something about going out towards the Tyrell Estate.” Sam shrugged. “They probably drove out there to see the gardens- he’s said it’s a good road to take his bike out on.”

Jon promptly spat out his entire sip of coffee, staining the front of his shirt as well as the back, and frightening little Sam enough that he started to cry.

“He took her on his motorcycle?”

Gilly picked that moment to reappear, completely clean and with wet hair, blinking at the scene in front of her.

Sam, who couldn’t seem to stop laughing, was desperately trying to calm down the baby, who had started wailing, while Jon’s entire front was covered in coffee and his entire back was covered in baby vomit. Not that he seemed to notice, as his face was white and he was making a series of angry looking hand gestures at her husband.

“I really can’t leave you three alone for five minutes, can I?” she sighed. “Do I even want to know?”

[waitineedaname]

Do you know if it was ever confirmed that Binghe was working with demons in Jinlian city era? We learn Zhuzhi-lang was responsible for the Sowers later and Binghe was only trying to be a righteous cultivator at Huan Hua during that time. I assumed that SQQ only thought he was building an empire in the demon realm because it happened in the original PIDW, and Binghe didn’t actually start that until after SQQ died. However, I see scenarios in fandom where Binghe is already established in the demon realm at the same time as the Jinlian city arc all the time. It’s a fun premise, and the fics are always good, but I was just wondering if it had a basis in canon or was just widely accepted fanon.

you know, that's a good question!! i'm really not sure?? I'd have to reread with a closer eye, but I think it's just widely accepted fanon on the basis of SQQ's assumptions based on what happened in PIDW! what we know for sure: three years pass between Binghe being thrown in the Abyss and him reuniting with SQQ in Jin Lan City (which is less time than in PIDW) and after the five years of SQQ's death, he has become established within the Demon Realm as a powerful demon lord (I think emperor by this point? can't remember). so that means either he was really busy after SQQ died, or he had some connections already due to his time in the Abyss!

it does raise a lot of questions about the timeline of events from Binghe's perspective! the pov being tied so tightly to SQQ means we miss out on a lot of what's going on with Binghe when he's not around. when did he fight and beat Mobei-Jun? when did Sha Hualing start working for him? when did he become established in his underground palace? he's so focused on SQQ that it's hard to imagine when he had the time to do a lot of this stuff. especially since in the five years of SQQ's death, he's making dinner every day and feeding the corpse spiritual energy. I have trouble imagining a man wracked with so much grief taking the time to kick Mobei-Jun's ass, but also he's the protagonist, he can do anything, so maybe I shouldn't be doubting his ability to multitask lol

[the-alternate-realities]

[stormsonjupiter]

The only three words women want to hear is, “accepted without revisions”.

[retrocgads]

USA 1997

[solarpunkpresentspodcast]

This episode’s guest is Dr Anne Pasek, Canada Research Chair in Media, Culture, and Environment, and an Assistant Professor in the Department of Cultural Studies and the School of the Environment at Trent University. Dr Pasek is co-founder of the Low Carbon Research Methods Group, and she talks to Ariel all about what Low Carbon Research is (and can look like!), the “carbon footprint” of academic research, new innovative ways for research to respond to the climate crisis, the importance of zines, and even hosting her own solar server in her backyard!

Links:

https://www.annepasek.com/

http://lowcarbonmethods.com/

https://emmlab.info/

http://solarprotocol.net/

[fabulaturbatory]

association for computing machinery conference advertisement, 1978 (via university of minnesota archives)

[ytmarketing001]

Another new video from our "AI Evolves" channel. Explore a future where hyper-realistic robots become indistinguishable from humans. Discover how these lifelike companions could change our lives, impact personal relationships, and reshape societal norms. Join us as we delve into the technology behind these robots, their potential roles in our daily lives, and the ethical considerations they raise. Stay up to date by subscribing to our channel. Please subscribe 🙏    / @aievolves  

[reallytoosublime]

Another new video from our "AI Evolves" channel. Explore a future where hyper-realistic robots become indistinguishable from humans. Discover how these lifelike companions could change our lives, impact personal relationships, and reshape societal norms. Join us as we delve into the technology behind these robots, their potential roles in our daily lives, and the ethical considerations they raise. Stay up to date by subscribing to our channel. Please subscribe 🙏    / @aievolves  

[jcmarchi]

Toward a code-breaking quantum computer

New Post has been published on https://thedigitalinsider.com/toward-a-code-breaking-quantum-computer/

Toward a code-breaking quantum computer

The most recent email you sent was likely encrypted using a tried-and-true method that relies on the idea that even the fastest computer would be unable to efficiently break a gigantic number into factors.

Quantum computers, on the other hand, promise to rapidly crack complex cryptographic systems that a classical computer might never be able to unravel. This promise is based on a quantum factoring algorithm proposed in 1994 by Peter Shor, who is now a professor at MIT.

But while researchers have taken great strides in the last 30 years, scientists have yet to build a quantum computer powerful enough to run Shor’s algorithm.

As some researchers work to build larger quantum computers, others have been trying to improve Shor’s algorithm so it could run on a smaller quantum circuit. About a year ago, New York University computer scientist Oded Regev proposed a major theoretical improvement. His algorithm could run faster, but the circuit would require more memory.

Building off those results, MIT researchers have proposed a best-of-both-worlds approach that combines the speed of Regev’s algorithm with the memory-efficiency of Shor’s. This new algorithm is as fast as Regev’s, requires fewer quantum building blocks known as qubits, and has a higher tolerance to quantum noise, which could make it more feasible to implement in practice.

In the long run, this new algorithm could inform the development of novel encryption methods that can withstand the code-breaking power of quantum computers.

“If large-scale quantum computers ever get built, then factoring is toast and we have to find something else to use for cryptography. But how real is this threat? Can we make quantum factoring practical? Our work could potentially bring us one step closer to a practical implementation,” says Vinod Vaikuntanathan, the Ford Foundation Professor of Engineering, a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), and senior author of a paper describing the algorithm.

The paper’s lead author is Seyoon Ragavan, a graduate student in the MIT Department of Electrical Engineering and Computer Science. The research will be presented at the 2024 International Cryptology Conference.

Cracking cryptography

To securely transmit messages over the internet, service providers like email clients and messaging apps typically rely on RSA, an encryption scheme invented by MIT researchers Ron Rivest, Adi Shamir, and Leonard Adleman in the 1970s (hence the name “RSA”). The system is based on the idea that factoring a 2,048-bit integer (a number with 617 digits) is too hard for a computer to do in a reasonable amount of time.

That idea was flipped on its head in 1994 when Shor, then working at Bell Labs, introduced an algorithm which proved that a quantum computer could factor quickly enough to break RSA cryptography.

“That was a turning point. But in 1994, nobody knew how to build a large enough quantum computer. And we’re still pretty far from there. Some people wonder if they will ever be built,” says Vaikuntanathan.

It is estimated that a quantum computer would need about 20 million qubits to run Shor’s algorithm. Right now, the largest quantum computers have around 1,100 qubits.

A quantum computer performs computations using quantum circuits, just like a classical computer uses classical circuits. Each quantum circuit is composed of a series of operations known as quantum gates. These quantum gates utilize qubits, which are the smallest building blocks of a quantum computer, to perform calculations.

But quantum gates introduce noise, so having fewer gates would improve a machine’s performance. Researchers have been striving to enhance Shor’s algorithm so it could be run on a smaller circuit with fewer quantum gates.

That is precisely what Regev did with the circuit he proposed a year ago.

“That was big news because it was the first real improvement to Shor’s circuit from 1994,” Vaikuntanathan says.

The quantum circuit Shor proposed has a size proportional to the square of the number being factored. That means if one were to factor a 2,048-bit integer, the circuit would need millions of gates.

Regev’s circuit requires significantly fewer quantum gates, but it needs many more qubits to provide enough memory. This presents a new problem.

“In a sense, some types of qubits are like apples or oranges. If you keep them around, they decay over time. You want to minimize the number of qubits you need to keep around,” explains Vaikuntanathan.

He heard Regev speak about his results at a workshop last August. At the end of his talk, Regev posed a question: Could someone improve his circuit so it needs fewer qubits? Vaikuntanathan and Ragavan took up that question.

Quantum ping-pong

To factor a very large number, a quantum circuit would need to run many times, performing operations that involve computing powers, like 2 to the power of 100.

But computing such large powers is costly and difficult to perform on a quantum computer, since quantum computers can only perform reversible operations. Squaring a number is not a reversible operation, so each time a number is squared, more quantum memory must be added to compute the next square.

The MIT researchers found a clever way to compute exponents using a series of Fibonacci numbers that requires simple multiplication, which is reversible, rather than squaring. Their method needs just two quantum memory units to compute any exponent.

“It is kind of like a ping-pong game, where we start with a number and then bounce back and forth, multiplying between two quantum memory registers,” Vaikuntanathan adds.

They also tackled the challenge of error correction. The circuits proposed by Shor and Regev require every quantum operation to be correct for their algorithm to work, Vaikuntanathan says. But error-free quantum gates would be infeasible on a real machine.

They overcame this problem using a technique to filter out corrupt results and only process the right ones.

The end-result is a circuit that is significantly more memory-efficient. Plus, their error correction technique would make the algorithm more practical to deploy.

“The authors resolve the two most important bottlenecks in the earlier quantum factoring algorithm. Although still not immediately practical, their work brings quantum factoring algorithms closer to reality,” adds Regev.

In the future, the researchers hope to make their algorithm even more efficient and, someday, use it to test factoring on a real quantum circuit.

“The elephant-in-the-room question after this work is: Does it actually bring us closer to breaking RSA cryptography? That is not clear just yet; these improvements currently only kick in when the integers are much larger than 2,048 bits. Can we push this algorithm and make it more feasible than Shor’s even for 2,048-bit integers?” says Ragavan.

This work is funded by an Akamai Presidential Fellowship, the U.S. Defense Advanced Research Projects Agency, the National Science Foundation, the MIT-IBM Watson AI Lab, a Thornton Family Faculty Research Innovation Fellowship, and a Simons Investigator Award.