#Democratization

[thepersonalwords]

I enjoy self-publishing & sending publishers rejection letters. They're like, 'Who is this guy?' And I'm like, 'the end of your industry.

Ryan Lilly, Write like no one is reading

[gregor-samsung]

택시운전사 [A Taxi Driver] (Jang Hoon, 2017)

[alewaanewspaper1960]

السياسة الخارجية الأمريكية وأزمات الترويج الديمقراطي - سوريا نموذجا

السياسة الخارجية الأمريكية وأزمات الترويج الديمقراطي – سوريا نموذجا   السياسة الخارجية الأمريكية وأزمات الترويج الديمقراطي – سوريا نموذجا american Foreign Policy And The Crises Of Democratic Promotion (model Of Syria) الكاتب : محوز عمر الملخص: شكّلت مسألة الترويج للديمقراطية أحد المبادئ والاهتمامات الرئيسية للسياسة الخارجية الأمريكية، حيث زخر الخطاب الأمريكي الرسمي برصيد معتبر من التعابير ذات…

[inapat17]

Traditions in transition: cinematic perspectives on the modernization of post-war societies (4/4)

Before concluding this four-part series, I want to examine how Lee Chang-dong’s "Peppermint Candy" (1999) portrays post-war South Korea’s transition from a military dictatorship to democracy. The film not only encapsulates the essence of societal transformation but also serves as a poignant reminder of history's lasting impact on individual lives.

As usual, you can find my previous articles HERE. 

Part 3. Peppermint Candy (박하사탕, Lee Chang-dong, 1999)

Peppermint Candy's Trailer

Directed by Lee Chang-dong, an influential auteur of Korea’s New Wave of cinema, Peppermint Candy (1999) reflects on South Korea’s turbulent journey to democratization and modernity in the decades after the Korean War. Through its non-linear structure and powerful performances, Lee Chang-dong's film delves deep into themes of lost innocence, the impact of political and social change, and the haunting effects of guilt and regret. By revealing Yong-ho’s life in reverse, Lee Chang-dong juxtaposes personal memories with historical events, emphasizing the interplay between individual trauma and collective memory. In this way, he also effectively highlights how past experiences shape present identities. 

The film begins with the suicide of the protagonist, Kim Yong-ho, who throws himself in front of an oncoming train. This haunting act serves as the catalyst for a reflective journey into the events that led to his untimely death. We see him in the 1990s as a broken middle-aged man, jobless due to the economic crisis and struggling with the consequences of his actions. His relationships deteriorate, including his failed marriage. Further back, he is depicted as a corrupt police officer and a disillusioned soldier witnessing the violent suppression of the “Gwangju Uprising”, also known as the “Gwangju Democratization Movement”. A tragic and pivotal incident in South Korean history that took place from May 18 to 27, 1980. 

Peppermint Candy, Lee Chang-dong, 1999

Triggered by widespread discontent with the authoritarian regime of Chun Doo-Hwan, thousands of students and civilians in the city of Gwangju protested against martial law and demanded democratic reforms. The military’s brutal response led to the death of hundreds of protesters and left a deep scar on the national consciousness. To this day, the Gwangju uprising remains a significant historical event, reflecting the nation’s turbulent journey towards democratization and the enduring impact of state violence on collective memory. 

Peppermint Candy, Lee Chang-dong, 1999

Peppermint Candy critiques political oppression and the abuse of power by depicting this military and police brutality. Its protagonist, Kim Yong-ho, is profoundly affected by the 1980 events. In a heart-wrenching scene, he accidently kills a high school girl during the chaos of the uprising, a moment that haunts him throughout the film. The title “Peppermint Candy” serves as a powerful symbol of innocence and nostalgia, contrasting sharply with Yong-ho’s despair. Initially, we see him as an idealistic young man with dreams and aspirations. However, as he becomes embroiled in the corrupt and violent system, his innocence is gradually stripped away, leaving him a hollow shell of his former self. Ultimately, Lee Chang-dong paints a harrowing portrait of a man haunted by his actions and struggling to reconcile the past with the present. Yong-ho’s identity crisis mirrors the broader societal identity crisis during South Korea’s transition. 

Thank you for accompanying me on this journey. Your support has been truly invaluable.

Ruth Sarfati

[jcmarchi]

From Recurrent Networks to GPT-4: Measuring Algorithmic Progress in Language Models - Technology Org

New Post has been published on https://thedigitalinsider.com/from-recurrent-networks-to-gpt-4-measuring-algorithmic-progress-in-language-models-technology-org/

From Recurrent Networks to GPT-4: Measuring Algorithmic Progress in Language Models - Technology Org

In 2012, the best language models were small recurrent networks that struggled to form coherent sentences. Fast forward to today, and large language models like GPT-4 outperform most students on the SAT. How has this rapid progress been possible? 

Image credit: MIT CSAIL

In a new paper, researchers from Epoch, MIT FutureTech, and Northeastern University set out to shed light on this question. Their research breaks down the drivers of progress in language models into two factors: scaling up the amount of compute used to train language models, and algorithmic innovations. In doing so, they perform the most extensive analysis of algorithmic progress in language models to date.

Their findings show that due to algorithmic improvements, the compute required to train a language model to a certain level of performance has been halving roughly every 8 months. “This result is crucial for understanding both historical and future progress in language models,” says Anson Ho, one of the two lead authors of the paper. “While scaling compute has been crucial, it’s only part of the puzzle. To get the full picture you need to consider algorithmic progress as well.”

The paper’s methodology is inspired by “neural scaling laws”: mathematical relationships that predict language model performance given certain quantities of compute, training data, or language model parameters. By compiling a dataset of over 200 language models since 2012, the authors fit a modified neural scaling law that accounts for algorithmic improvements over time. 

Based on this fitted model, the authors do a performance attribution analysis, finding that scaling compute has been more important than algorithmic innovations for improved performance in language modeling. In fact, they find that the relative importance of algorithmic improvements has decreased over time. “This doesn’t necessarily imply that algorithmic innovations have been slowing down,” says Tamay Besiroglu, who also co-led the paper.

“Our preferred explanation is that algorithmic progress has remained at a roughly constant rate, but compute has been scaled up substantially, making the former seem relatively less important.” The authors’ calculations support this framing, where they find an acceleration in compute growth, but no evidence of a speedup or slowdown in algorithmic improvements.

By modifying the model slightly, they also quantified the significance of a key innovation in the history of machine learning: the Transformer, which has become the dominant language model architecture since its introduction in 2017. The authors find that the efficiency gains offered by the Transformer correspond to almost two years of algorithmic progress in the field, underscoring the significance of its invention.

While extensive, the study has several limitations. “One recurring issue we had was the lack of quality data, which can make the model hard to fit,” says Ho. “Our approach also doesn’t measure algorithmic progress on downstream tasks like coding and math problems, which language models can be tuned to perform.”

Despite these shortcomings, their work is a major step forward in understanding the drivers of progress in AI. Their results help shed light about how future developments in AI might play out, with important implications for AI policy. “This work, led by Anson and Tamay, has important implications for the democratization of AI,” said Neil Thompson, a coauthor and Director of MIT FutureTech. “These efficiency improvements mean that each year levels of AI performance that were out of reach become accessible to more users.”

“LLMs have been improving at a breakneck pace in recent years. This paper presents the most thorough analysis to date of the relative contributions of hardware and algorithmic innovations to the progress in LLM performance,” says Open Philanthropy Research Fellow Lukas Finnveden, who was not involved in the paper.

“This is a question that I care about a great deal, since it directly informs what pace of further progress we should expect in the future, which will help society prepare for these advancements. The authors fit a number of statistical models to a large dataset of historical LLM evaluations and use extensive cross-validation to select a model with strong predictive performance. They also provide a good sense of how the results would vary under different reasonable assumptions, by doing many robustness checks. Overall, the results suggest that increases in compute have been and will keep being responsible for the majority of LLM progress as long as compute budgets keep rising by ≥4x per year. However, algorithmic progress is significant and could make up the majority of progress if the pace of increasing investments slows down.”

Written by Rachel Gordon

Source: Massachusetts Institute of Technology

You can offer your link to a page which is relevant to the topic of this post.

[taqato-alim]

Extrapolation of the potential effects of generative AI based on the effects of the invention of the printing press

Here are some of the major historical events closely related to the invention of the printing press:

Gutenberg Bible (1455): Considered the earliest surviving book printed with movable metal type in Europe. This was Johannes Gutenberg's magnum opus and demonstrated the viability of printing. It helped spread the printing press technology across Europe rapidly.

Spread of Humanism (15th century): The rise of humanism emphasized classical learning and education of the population. This created demand for books which fueled the growth of printing. Works of scholars like Erasmus were widely printed and disseminated.

Protestant Reformation (16th century): Martin Luther effectively used the printing press to mass produce and distribute his 95 Theses and other writings criticizing the Catholic church. This helped spark the Protestant Reformation movement by disseminating ideas to a wider audience.

Decline of scriptoria (15th century): As the printing press became dominant, it replaced handwritten manuscript production in scriptoria attached to monasteries. This was a major cultural shift from manuscript to print culture.

Vernacular literature (15th-16th century): The printing press enabled literature to be published in local languages rather than just Latin, making it accessible to the general populace and helping establish national identities and cultures.

Scientific revolution (16th-17th century): New scientific ideas could be widely shared through printing, accelerating processes of data collection, experimentation and debate. This was instrumental to the scientific revolution.

In summary, the printing press was a key driver of the dissemination of ideas during major social, religious and intellectual changes in the early modern period in Europe. It helped enable the spread of humanism, Reformation, rise of vernacular languages and acceleration of scientific progress.

Here is an extrapolation of the potential effects of generative AI based on the effects of the invention of the printing press:

Democratization of content creation: Generative AI tools may allow more people to easily generate all kinds of creative works like images, videos, writing, music etc. This could mirror how printing expanded authorship.

Accelerated spread of ideas: AI-generated content could propagate new concepts rapidly online, just as printing disseminated humanist texts and revolutionary writings more broadly.

Shift from scarcity to abundance: Generating AI may replace scarce, costly manual production with abundant, cheap automated creation like printing replaced hand-copied manuscripts. This could impact creative industries.

Empowerment of grassroots movements: Citizen-led causes may leverage AI tools to amplify messages through generated visuals/narratives online, paralleling how printing aided reformers like Luther.

Rise of AI-generated literature: Entire books, stories, poems could be algorithmically written, analogous to printed vernacular texts establishing new cultural forms.

Democratization of knowledge: Open-source generative models may make specialized expertise like science/medicine/law more accessible to all through synthesized content.

Accelerated scientific progress: AI models generate hypothesis, analyze data at vast scales, freeing up researchers to confirm/falsify ideas faster through collaborative online science like printing sped up process.

Changes to intellectual property: Widespread AI generation may challenge existing models of ownership over creative works as printing did for copying manuscripts.

Of course, there are also risks such as misuse, bias, and economic disruption to consider with generative AI that echo concerns raised historically over printing technologies.

Overall impacts will depend on how generative tools are developed and governed.

r56CCGBPsF1s1g1lQ5PX

[pomeraniandancer]

I'm taking a class focusing on democratic government and democratization. One of the things we've been discussing are the various democracy indexes that evaluate and index the level of democracy in every recognized nation in the world (plus a couple extra, like breakaway territories and the like). One of the things that is measured to determine the degree of democratic freedom in a given nation is how they treat their minorities and how much freedom and access they have in the country. One of the indexes we've been working with is Freedom House, which releases its new index every year at the end of February, so we'll be working with the new release (which is basically the political science equivalent of the Superbowl for democracy specialists) when we get back from Spring break. I'll have to ask my professor if the recognition of same-sex marriage in Greece has had any impact on its democracy score. It's actually one of the nations we've been discussing in class, since it was part of a democratization wave in the 1970's. And, of course, a huge Congratulations to the happy couple!

Greek novelist Auguste Corteau and his husband Anastasios Samouilidis, the first homosexual couple to be married at Athens' city hall, March 7th 2024

[thashining]

What the media won't show

[beauty-funny-trippy]

[itsallpoliticsstupid]

So many people are finding screenshots of celebrities allegedly doing a 'nazi salute,' to try and discredit what people have been saying about Elon Musk.

My favourite most recently has been a picture of Sabrina Carpenter which can easily be discredited.

This is the picture:

And this is the video:

Yep, it's just a young woman waving to her fans.

And this is why when you ask any of them who post the screenshots for a video, they refuse to add it in. Because they know the video is of somebody doing something very normal.

We are so absolutely screwed.

[bump-inthe-night]

If it makes any of you feel better, Donald Trump will have an uphill battle to change the constitution. He will need:

-2/3 of Senators (67)

-2/3 of the House of Representatives (290)

-3/4 of the states (38)

In 2026, 33 senate seats will be up for grabs, and we’ll be able to vote for people who are against Trump and his ideals.

Breathe and remain hopeful because it’s not over. We can still fight and make Trump’s last four years hell.

[mysharona1987]

[soberscientistlife]

[steelbluehome]

I'd just like to clarify some things about Senator Cory Booker's marathon Senate speech in protest of the present administration and everything they are doing to the American people.

Senator Booker was NOT allowed to sit down, eat, or use the bathroom during his speech. Sitting or leaving the room to use the bathroom would be considered yielding the floor. Eating would have interfered with his speaking and the person who has the floor must continue to speak, except when listening to questions that they will then answer.

He only took occasional sips of water.

The person who previously held the record for longest speech on the Senate floor did have bathroom breaks and also did things like read from the encyclopedia.

Senator Booker did not do that. His speech was to point out the damage that this administration is doing and he stayed on that subject.

Senator Booker's speech did reach many people. It wasn't a silly stunt that was done so that he could take the record for longest speech. He wanted to show the country that democrats will do something to bring attention to the problems we are facing. That democrats are listening to them.

Senator Cory Booker spoke for 25 hours and 4 minutes to "make good trouble."

ETA Thanks for all of the reblogs and notes! I hadn't wanted to dirty this post with the name of the former holder of the record for longest time holding the Senate floor, but there are a lot of questions.

Senator Strom Thurmond, a segregationist and white supremacist, held the previous record of 24 hours and 18 minutes when he filibustered the vote on the Civil Rights Act.

Sen. Thurmond had someone put a bucket just outside of the doorway to the cloakroom so that he could keep one foot on the floor while pissing into this bucket, to hold the floor.

Senator Booker would never disrespect the Senate, nor "bend the rules" in such a way.

Because of this Sen. Thurmond could drink coffee or anything else he wanted, as much as he wanted, to keep himself awake, soothe his throat, and keep his mouth from becoming dry.

Senator Booker limited himself to a few sips at a time from two glasses of water at the podium.

Also, Sen. Thurmond began his speech immediately before a vote was to be taken and his speech was specifically to delay that vote. That is the definition of a "filibuster".

Senator Booker's speech was not designed to delay or prevent any vote. He did not know how long he would be physically able to speak. Therefore, his was a speech, not a filibuster.

ETA2: Strom Thurmond did also temporarily yield the floor to a colleague and took a bathroom break at that time. He also had some rye bread and hamburger to eat.

Source

ETA3: So sorry about all of these but I need to include just one more thing.

This is the transcript of Strom Thurmond's filibuster

He read the voting laws of all 48 states (this was 1957). He read from a book called "The History of the Jury Trial" speaking for quite some time about things like the justice system of the Anglo-Saxons. He read from other books, he read from the Declaration of Independence, he read from the Constitution. He yielded the floor for someone to be sworn in. All kinds of things about his filibuster made Senator Booker's speech a far superior feat, not just because it lasted longer.

[politijohn]

It’s not lost on me that Bernie Sanders is the only mainstream politician touring the country rn listening to Americans’ concerns, giving them hope that a better world is still possible. Not campaigning for President, not an election year, just inspiring swing town voters to use their power to incite change in their communities.

Bernie is 83yo, doing the work that every single Democrat could be doing simply in their own district. He’s packing overflow rooms by the thousands in suburban and rural towns, not “democratic strongholds”. It is possible to get through the next four years but the status quo Dems aren’t going to make that happen.

Imagine what a true progressive party could do for the US. Leftist policy is popular and wins elections. Bernie and others have told us this for decades. If you tuned out his message before, I have to wonder what side you’re truly on. Because his shtick has not wavered with everyday Americans.

Not me, us.