The work on splitting the source code ordered by TikTok’s Chinese parent ByteDance late last year predated a bill to force a sale of TikTok&#x27;s U.S. operations that began gaining steam in Congress this year. The bill was signed into law in April.

Exclusive: TikTok preparing a US copy of the app’s core algorithm, sources say | Reuters

In their legal challenge, TikTok and ByteDance argue the sale-or-ban law violates the First Amendment by suppressing a platform Americans use for information and self-expression. Courts traditionally evaluate such speech disputes on whether the government is pursuing a compelling state interest ...

Biden administration took a pass on a plan to make TikTok safer - The Washington Post

The move, which may catch many merchants in the region by surprise, reflects ByteDance’s objective of entrenching itself in the US as a way to prove its value to domestic merchants and consumers.

TikTok pauses e-commerce push into Europe to focus on US - CNBC TV18

Layoffs in the wake of a major restructuring are not necessarily a surprise, though several ex-staffers told BI they wondered whether last week&#x27;s cuts were accelerated by the US divest-or-ban law that passed in April and would force TikTok&#x27;s owner ByteDance to divest from its US assets.

Laid-off TikTok staffers describe feeling 'blindsided' after a 'very chaotic ride'

ByteDance Ltd.’s social media startup has put on hold a rollout of its shopping platform across Spain, Germany, Italy, France and Ireland that was to have taken place as soon as July, according to people familiar with the matter. It also iced plans to bring the Shop feature to Mexico and ...

TikTok Pauses E-Commerce Push into Europe to Focus on US - Bloomberg

ByteDance has called on Chinese social media not to spread such misinformation after declaring the report as untrue.

ByteDance rejects US report about its purported plan since 2022 to divest TikTok’s operations in America | South China Morning Post

In response to a recent US law requiring China-based ByteDance to divest from its US holdings and sell TikTok’s American-based operations, O’Leary posted an item on the StartEngine crowdfunding site titled “Mr. Wonderful’s Plan to Buy TikTok.”

'Shark Tank' star Kevin O'Leary wants to buy TikTok in crowdfunded deal

When President Biden signed the TikTok ban into effect in April, the clock began for parent company ByteDance to either divest from the app or see it banned in the country. The bill gave ByteDance a timeline to sell its stake to a non-Chinese buyer before January 19, 2025.

US TikTok Ban Heads to Appeals Court This September | Hypebeast

Get the most recent info and news about ByteDance on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

Inspire creativity, enrich life.

ByteDance is a technology company operating a range of content platforms that inform, educate, entertain and inspire people across languages, cultures, and geographies.

Dedicated to building global platforms of creation and interaction, ByteDance now has a portfolio of applications available in over 150 markets and 75 languages. For example, TikTok, Helo, Vigo Video, Douyin, and Huoshan.

ByteDance's platforms aim to help users explore and discover the world's creativity, knowledge and moments that matter in everyday life while empowering everyone to be a creator directly from their smartphones. We are committed to building a safe, healthy and positive online environment for all our users.

We welcome people from all backgrounds to join us. If tackling challenges in a fast-changing industry does not scare you, work with us and challenge yourself to move the world!

ByteDance

Is ByteDance’s Lumi an AI Experiment Disguised as an AI Creator Community?

ByteDance's Lumi የ AI ሙከራ እንደ AI ፈጣሪ ማህበረሰብ ተደብቋል?

¿Es Lumi de ByteDance un experimento de IA disfrazado de comunidad de creadores de IA?

Èske Lumi ByteDance a se yon eksperyans AI degize kòm yon kominote kreyatè AI?

Արդյո՞ք ByteDance-ի Lumi-ն AI փորձ է, որը քողարկված է որպես AI Ստեղծողների համայնք:

ByteDance の Lumi は AI クリエイター コミュニティを装った AI 実験なのか?

ByteDance의 Lumi는 AI 크리에이터 커뮤니티로 위장한 AI 실험일까요?

ByteDance’s Lumi ezali Expérience ya AI oyo e déguisé lokola Communauté ya Créateur ya AI?

Lumi ຂອງ ByteDance ເປັນການທົດລອງ AI ປອມຕົວເປັນຊຸມຊົນຜູ້ສ້າງ AI ບໍ?

Adakah Lumi ByteDance merupakan Eksperimen AI yang Menyamar sebagai Komuniti Pencipta AI?

Je, Lumi ya ByteDance ni Jaribio la AI Limefichwa kama Jumuiya ya Watayarishi wa AI?

Оё Lumi byteDance як озмоиши AI аст, ки ҳамчун ҷомеаи Офарандаи AI пинҳон карда шудааст?

Ngaba i-ByteDance's Lumi liLingelo le-AI eliguqulelwe njengoluntu lwabadali be-AI?

ByteDance Bets Big: A Strategic Exit From The Social Media Circus With AI Video?

ባይት ዳንስ ትልቅ፡ ከማህበራዊ ሚዲያ ሰርከስ በ AI ቪዲዮ ስልታዊ መውጣት?

ByteDance залага много: Стратегическо излизане от цирка на социалните медии с AI Video?

ByteDance se kladi na veliko: Strateški izlaz iz cirkusa društvenih medija sa AI videom?

ByteDance apuesta a lo grande: ¿una salida estratégica del circo de las redes sociales con vídeos de inteligencia artificial?

ByteDance mise gros : une sortie stratégique du cirque des médias sociaux avec la vidéo IA ?

ByteDance הימר בגדול: יציאה אסטרטגית מקרקס המדיה החברתית עם וידאו בינה מלאכותית?

ByteDance が大きな賭けに出る: AI ビデオでソーシャル メディア サーカスから戦略的に撤退か?

ByteDance Bets Big: Jalan Keluar Strategik Dari Circus Media Sosial Dengan Video AI?

ByteDance zet hoog in: een strategische uitweg uit het sociale mediacircus met AI-video?

ByteDance Hatun Apuestas: ¿Huk Estratégico Lluqsiy Circo de Medios Socialesmanta AI Videowan?

ByteDance katta tikish: AI video bilan ijtimoiy media sirkidan strategik chiqishmi?

I-ByteDance Ukubheja Okukhulu: Ukuphuma Okuyisu Kusuka Kusekisini Yezokuxhumana Ngevidiyo ye-AI?

Tiktok Inc., and ByteDance LTD., v. Merrick B. Garland Update Court Filing, retrieved on May 7, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 10 of 11. Ground 4: Unconstitutional Taking 110. The Act effects an unlawful taking of private property without just compensation, in violation of the Fifth Amendment’s Takings Clause. 111. The Takings Clause provides that “private property” shall not be “taken for public use, without just compensation.” U.S. Const. amend. V, cl. 5. The Act does just that by shutting down ByteDance’s U.S. businesses or, to the extent any qualified divestiture alternative is even feasible (it is not), compelling ByteDance to sell those businesses under fire-sale circumstances that guarantee inadequate compensation. 112. Petitioners have substantial property interests in, and associated with, their and their affiliates’ U.S. operations. These include not only ByteDance Ltd.’s interest in TikTok Inc. and other U.S. businesses, but also the platforms and applications themselves. See Kimball Laundry Co. v. United States, 338 U.S. 1, 11–13 (1949) (Takings Clause also protects losses to going-concern value of business). 113. If the Act’s prohibitions take effect, they will deprive Petitioners of property protected by the Takings Clause. Absent a qualified divestiture, the Act will shutter Petitioners’ businesses in the United States. And even if a qualified divestiture were feasible (it is not), any sale could be, at best, completed only at an enormous discount to the U.S. businesses’ current market value, given the forced sale conditions. See BFP v. Resol. Tr. Corp., 511 U.S. 531, 537 (1994) (“[M]arket value, as it is commonly understood, has no applicability in the forced-sale context; indeed, it is the very antithesis of forced-sale value.”). 114. Because the Act compels ByteDance “to relinquish specific, identifiable property” or forfeit “all economically beneficial uses,” the Act effects a per se taking. Horne v. Dep’t of Agric., 576 U.S. 350, 364–65 (2015); Lucas v. S.C. Coastal Council, 505 U.S. 1003, 1019 (1992). 115. Alternatively, the Act inflicts a regulatory taking. Even when a law does not compel the physical invasion of property or deprive the property of all economically viable use, it still effects a taking “if [it] goes too far.” Penn. Coal Co. v. Mahon, 260 U.S. 393, 415 (1922). In determining when a law “goes too far,” courts have typically looked to “several factors” identified in Penn Central Transportation Co. v. City of New York, 438 U.S. 104, 124 (1978), namely, (a) “[t]he economic impact of the regulation”; (b) “the extent to which the regulation has interfered with reasonable investment-backed expectations”; and (c) “the character of the governmental action.” The Act inflicts a regulatory taking under each of these three factors. 116. The Act does not compensate Petitioners (let alone provide just compensation) for the dispossession of their U.S. businesses. See United States v. Miller, 317 U.S. 369, 373 (1943). Prospective injunctive relief is accordingly warranted. See, e.g., Youngstown Sheet & Tube Co. v. Sawyer, 343 U.S. 579, 585 (1952). Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on May 7, 2024, from sf16-va.tiktokcdn.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. Tiktok Inc., and ByteDance LTD., v. Merrick B. Garland Update Court Filing, retrieved on May 7, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 10 of 11. Tiktok Inc., and ByteDance LTD., v. Merrick B. Garland Update Court Filing, retrieved on May 7, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 10 of 11. HackerNoon’s Legal PDF Series here Ground 4: Unconstitutional Taking 110. The Act effects an unlawful taking of private property without just compensation, in violation of the Fifth Amendment’s Takings Clause. 111. The Takings Clause provides that “private property” shall not be “taken for public use, without just compensation.” U.S. Const. amend. V, cl. 5. The Act does just that by shutting down ByteDance’s U.S. businesses or, to the extent any qualified divestiture alternative is even feasible (it is not), compelling ByteDance to sell those businesses under fire-sale circumstances that guarantee inadequate compensation. 112. Petitioners have substantial property interests in, and associated with, their and their affiliates’ U.S. operations. These include not only ByteDance Ltd.’s interest in TikTok Inc. and other U.S. businesses, but also the platforms and applications themselves. See Kimball Laundry Co. v. United States, 338 U.S. 1, 11–13 (1949) (Takings Clause also protects losses to going-concern value of business). 113. If the Act’s prohibitions take effect, they will deprive Petitioners of property protected by the Takings Clause. Absent a qualified divestiture, the Act will shutter Petitioners’ businesses in the United States. And even if a qualified divestiture were feasible (it is not), any sale could be, at best, completed only at an enormous discount to the U.S. businesses’ current market value, given the forced sale conditions. See BFP v. Resol. Tr. Corp., 511 U.S. 531, 537 (1994) (“[M]arket value, as it is commonly understood, has no applicability in the forced-sale context; indeed, it is the very antithesis of forced-sale value.”). 114. Because the Act compels ByteDance “to relinquish specific, identifiable property” or forfeit “all economically beneficial uses,” the Act effects a per se taking. Horne v. Dep’t of Agric., 576 U.S. 350, 364–65 (2015); Lucas v. S.C. Coastal Council, 505 U.S. 1003, 1019 (1992). 115. Alternatively, the Act inflicts a regulatory taking. Even when a law does not compel the physical invasion of property or deprive the property of all economically viable use, it still effects a taking “if [it] goes too far.” Penn. Coal Co. v. Mahon, 260 U.S. 393, 415 (1922). In determining when a law “goes too far,” courts have typically looked to “several factors” identified in Penn Central Transportation Co. v. City of New York, 438 U.S. 104, 124 (1978), namely, (a) “[t]he economic impact of the regulation”; (b) “the extent to which the regulation has interfered with reasonable investment-backed expectations”; and (c) “the character of the governmental action.” The Act inflicts a regulatory taking under each of these three factors. 116. The Act does not compensate Petitioners (let alone provide just compensation) for the dispossession of their U.S. businesses. See United States v. Miller, 317 U.S. 369, 373 (1943). Prospective injunctive relief is accordingly warranted. See, e.g., Youngstown Sheet & Tube Co. v. Sawyer, 343 U.S. 579, 585 (1952). Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on May 7, 2024, from sf16-va.tiktokcdn.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on May 7, 2024, from sf16-va.tiktokcdn.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. sf16-va.tiktokcdn.com

ByteDance's Fight Against Forced Sale Circumstances

Ticked Off: A Dark Web Researcher's Perspective on TikTok's Controversy

Since March 13, 2024, when the U.S. House of Representatives passed a bill for a nationwide ban on the popular social media platform TikTok, conspiracy theories about the ban have been spreading across the internet. TikTok's parent company, ByteDance, headquartered in China, was given six months to find a new buyer to avoid the app’s removal from U.S. app stores. TikTok's last-ditch effort to file a lawsuit failed on Friday when the Supreme Court ruled that the law did not violate the First Amendment. And just like that, six months flew by in the blink of an eye. Facing the ban on Sunday, January 19, 2025, TikTok decided to voluntarily shut down its service for U.S. users. Apple and Google Play promptly removed the app, leaving users who opened TikTok greeted with a bitter farewell message. Biden's White House declared that enforcing the ban would be left to the incoming Trump administration. For his part, President-elect Donald Trump swore to “save” TikTok. True to his word, Trump extended the ban’s effective date by 75 days after taking office. The 170 million TikTok users in the U.S. rejoiced to have access to their beloved app. Despite being just a 12-hour ban, the shutdown caused global panic. For millions, the platform was more than an app; it was a career, creative outlet, and community. The chaos led panicked users to call 911, prompting officials to urge the public to stop misusing emergency lines, as it diverted resources from real crises. Additionally, influencers and extremists across the political spectrum speculated that the ban was driven by shadowy groups with hidden agendas, not just security concerns. Spy Conspiracy Theory According to the ban bill, the main issue with TikTok is that it’s owned by a so-called "foreign adversary," posing a national security threat. U.S. officials have repeatedly raised concerns that the Chinese government could exploit TikTok for spying on Americans or covertly influencing public opinion by amplifying or suppressing certain content. The paranoia is justified, they argue, due to China's laws requiring organizations to aid in intelligence gathering. FBI Director Christopher Wray warned that TikTok's software might enable the Chinese government to access Americans' devices. Republican Senator Josh Hawley from Missouri passionately echoed these concerns in a fiery speech: “If you’ve got TikTok on your phone right now, it can track your location, read your text messages, monitor your keystrokes. It has access to your phone’s recordings. This isn’t just a national security threat — it’s a personal safety threat.” Canadian-American venture capitalist Chamath Palihapitiya added to the controversy on X, stating that the unanimous Supreme Court decision to uphold the ban, supported by a bipartisan majority, suggests that "the U.S. determined that TikTok is spyware for a foreign entity." This theory sent X users into a heated debate. Some backed Palihapitiya, agreeing that TikTok might indeed be spyware. One supporter proved: “I genuinely don’t understand the fight to keep TikTok in the U.S. It’s literally Chinese spyware that China doesn’t even let its kids use. It’s a weapon harming our children. Still trying to figure out any argument for keeping it online—unless it’s because some wealthy GOP donors stand to lose big.” Others agreed, labeling the platform a “security threat,” while skeptics fired back, insisting there’s no hard evidence to support these claims. Zionist Conspiracy Theory Another wild theory capturing the imagination of certain corners of the internet is the claim that the “Jewish lobby” wants to control TikTok. Influencer and streamer Haz Al-Din, also known as Infrared, suggested that the TikTok ban isn’t about China at all but rather about handing “control over to Israel in the interests of the ‘Zionist lobby.’” Similarly, antisemitic influencer Vincent James took to X to share with his nearly 60,000 followers that “the Jews want complete control over information.” This claim feeds into a broader narrative that Israel is allegedly leveraging its supposed influence to push for a TikTok ban and suppress pro-Palestinian content. As “evidence,” conspiracy theorists point to data from OpenSecrets, which lists donations from AIPAC (the American Israel Public Affairs Committee) to Republican Congressman Mike Gallagher, who led the charge on the TikTok bill. Proponents of the theory argue this is proof that Israel and Mossad are influencing U.S. government decisions regarding TikTok. They emphasize that the bill’s sponsor allegedly received “significant contributions from Zionists.” There is no evidence linking AIPAC to the drafting of the legislation. Antisemite Stew Peters baselessly claims that "Zionist extortion teams" are behind anti-TikTok legislation, alleging it's because the platform allows users to question Israel. In his videos, Peters calls for the destruction of Zionism. Fortunately, his reach on Rumble is limited, with only a few thousand subscribers and his videos rarely exceed 500 views. Who Controls Information Controls the World We've detailed the prominent conspiracy theories about TikTok's closure, ranging from Zionist influence to Chinese espionage fears. Despite their popularity, there's little evidence supporting these claims, as TikTok hasn't been proven to share data with the Chinese Communist government. Republican Senator Rand Paul of Kentucky summed it up perfectly: "Most of the reasons the government banned it were based on accusations, not evidence." But what about actual data from real surveys? A study by the Allensbach Institute in Germany indicates that TikTok's informational ecosystem may foster skepticism and amplify conspiracy theories. Germans using TikTok for news are less likely to view China as a dictatorship, criticize Russia's invasion of Ukraine, or trust vaccines compared to traditional media consumers. While 57% of newspaper readers see China as a dictatorship, only 28.1% of TikTok users agree. TikTok users are also less likely to believe that China and Russia spread disinformation and are more suspicious of their governments. The influence of foreign powers on social media is undeniable, emphasizing the adage, "Who controls information controls the world." The question is not who controls the app, but who controls how we perceive the information we consume. Since March 13, 2024, when the U.S. House of Representatives passed a bill for a nationwide ban on the popular social media platform TikTok, conspiracy theories about the ban have been spreading across the internet. passed a bill TikTok's parent company, ByteDance, headquartered in China, was given six months to find a new buyer to avoid the app’s removal from U.S. app stores. TikTok's last-ditch effort to file a lawsuit failed on Friday when the Supreme Court ruled that the law did not violate the First Amendment. Supreme Court ruled that the law did not violate the First Amendment. And just like that, six months flew by in the blink of an eye. Facing the ban on Sunday, January 19, 2025, TikTok decided to voluntarily shut down its service for U.S. users. Apple and Google Play promptly removed the app, leaving users who opened TikTok greeted with a bitter farewell message. with a bitter farewell message. Biden's White House declared that enforcing the ban would be left to the incoming Trump administration. For his part, President-elect Donald Trump swore to “save” TikTok. True to his word, Trump extended the ban’s effective date by 75 days after taking office. Trump extended the ban’s effective date by 75 days The 170 million TikTok users in the U.S. rejoiced to have access to their beloved app. Despite being just a 12-hour ban, the shutdown caused global panic. For millions, the platform was more than an app; it was a career, creative outlet, and community. The chaos led panicked users to call 911 , prompting officials to urge the public to stop misusing emergency lines, as it diverted resources from real crises. Additionally, influencers and extremists across the political spectrum speculated that the ban was driven by shadowy groups with hidden agendas, not just security concerns. users to call 911 Spy Conspiracy Theory According to the ban bill, the main issue with TikTok is that it’s owned by a so-called "foreign adversary," posing a national security threat. U.S. officials have repeatedly raised concerns that the Chinese government could exploit TikTok for spying on Americans or covertly influencing public opinion by amplifying or suppressing certain content. repeatedly raised concerns The paranoia is justified, they argue, due to China's laws requiring organizations to aid in intelligence gathering. FBI Director Christopher Wray warned that TikTok's software might enable the Chinese government to access Americans' devices. Republican Senator Josh Hawley from Missouri passionately echoed these concerns in a fiery speech: echoed these concerns “If you’ve got TikTok on your phone right now, it can track your location, read your text messages, monitor your keystrokes. It has access to your phone’s recordings. This isn’t just a national security threat — it’s a personal safety threat.” “If you’ve got TikTok on your phone right now, it can track your location, read your text messages, monitor your keystrokes. It has access to your phone’s recordings. This isn’t just a national security threat — it’s a personal safety threat.” “If you’ve got TikTok on your phone right now, it can track your location, read your text messages, monitor your keystrokes. It has access to your phone’s recordings. This isn’t just a national security threat — it’s a personal safety threat.” Canadian-American venture capitalist Chamath Palihapitiya added to the controversy on X , stating that the unanimous Supreme Court decision to uphold the ban, supported by a bipartisan majority, suggests that "the U.S. determined that TikTok is spyware for a foreign entity." to the controversy on X This theory sent X users into a heated debate. Some backed Palihapitiya, agreeing that TikTok might indeed be spyware. One supporter proved: One supporter proved: “I genuinely don’t understand the fight to keep TikTok in the U.S. It’s literally Chinese spyware that China doesn’t even let its kids use. It’s a weapon harming our children. Still trying to figure out any argument for keeping it online—unless it’s because some wealthy GOP donors stand to lose big.” “I genuinely don’t understand the fight to keep TikTok in the U.S. It’s literally Chinese spyware that China doesn’t even let its kids use. It’s a weapon harming our children. Still trying to figure out any argument for keeping it online—unless it’s because some wealthy GOP donors stand to lose big.” “I genuinely don’t understand the fight to keep TikTok in the U.S. It’s literally Chinese spyware that China doesn’t even let its kids use. It’s a weapon harming our children. Still trying to figure out any argument for keeping it online—unless it’s because some wealthy GOP donors stand to lose big.” Others agreed, labeling the platform a “security threat,” while skeptics fired back, insisting there’s no hard evidence to support these claims. Zionist Conspiracy Theory Another wild theory capturing the imagination of certain corners of the internet is the claim that the “Jewish lobby” wants to control TikTok. Influencer and streamer Haz Al-Din, also known as Infrared, suggested that the TikTok ban isn’t about China at all but rather about handing “control over to Israel in the interests of the ‘Zionist lobby.’” suggested that the TikTok ban isn’t about China Similarly, antisemitic influencer Vincent James took to X to share with his nearly 60,000 followers that “the Jews want complete control over information.” took to X to share This claim feeds into a broader narrative that Israel is allegedly leveraging its supposed influence to push for a TikTok ban and suppress pro-Palestinian content. As “evidence,” conspiracy theorists point to data from OpenSecrets , which lists donations from AIPAC (the American Israel Public Affairs Committee) to Republican Congressman Mike Gallagher, who led the charge on the TikTok bill. Proponents of the theory argue this is proof that Israel and Mossad are influencing U.S. government decisions regarding TikTok. They emphasize that the bill’s sponsor allegedly received “significant contributions from Zionists.” data from OpenSecrets There is no evidence linking AIPAC to the drafting of the legislation. Antisemite Stew Peters baselessly claims that "Zionist extortion teams" are behind anti-TikTok legislation, alleging it's because the platform allows users to question Israel. In his videos, Peters calls for the destruction of Zionism. Fortunately, his reach on Rumble is limited, with only a few thousand subscribers and his videos rarely exceed 500 views. claims that Who Controls Information Controls the World We've detailed the prominent conspiracy theories about TikTok's closure, ranging from Zionist influence to Chinese espionage fears. Despite their popularity, there's little evidence supporting these claims, as TikTok hasn't been proven to share data with the Chinese Communist government. Republican Senator Rand Paul of Kentucky summed it up perfectly: "Most of the reasons the government banned it were based on accusations, not evidence." "Most of the reasons the government banned it were based on accusations, not evidence." "Most of the reasons the government banned it were based on accusations, not evidence." But what about actual data from real surveys? A study by the Allensbach Institute in Germany indicates that TikTok's informational ecosystem may foster skepticism and amplify conspiracy theories. Germans using TikTok for news are less likely to view China as a dictatorship, criticize Russia's invasion of Ukraine, or trust vaccines compared to traditional media consumers. While 57% of newspaper readers see China as a dictatorship, only 28.1% of TikTok users agree. TikTok users are also less likely to believe that China and Russia spread disinformation and are more suspicious of their governments. The influence of foreign powers on social media is undeniable, emphasizing the adage, study by the Allensbach Institute in Germany "Who controls information controls the world." "Who controls information controls the world." The question is not who controls the app, but who controls how we perceive the information we consume.

Is the TikTok Ban a Cover-Up? The Internet Thinks So

টিকটক নিষিদ্ধ করা কি কেবলই একটা ধামাচাপা দেওয়া? ইন্টারনেট তাই মনে করে

Ist das TikTok-Verbot eine Vertuschung? Das Internet glaubt das

¿Es la prohibición de TikTok un encubrimiento? Internet así lo cree

L'interdiction de TikTok est-elle une dissimulation ? Internet le pense

क्या TikTok पर प्रतिबंध एक कवर-अप है? इंटरनेट ऐसा सोचता है

TikTok禁止は隠蔽か？ネットではそう思われている

TikTok 금지령은 은폐일까? 인터넷은 그렇게 생각한다

A proibição do TikTok é um encobrimento? A Internet pensa assim

Является ли запрет TikTok прикрытием? Так думает Интернет

TikTok Yasağı Bir Örtbas Etme mi? İnternet Öyle Düşünüyor

Lệnh cấm TikTok có phải là một sự che đậy không? Internet nghĩ vậy

TikTok 禁令是掩盖事实吗？互联网认为如此

DeepSeek's Janus Pro, OpenAI o3-mini, Mistral's 24B Parameter Model, and More

Table of Links Abstract and 1 Introduction 2 Related Works 3 Method and 3.1 Proxy-Guided 3D Conditioning for Diffusion 3.2 Interactive Generation Workflow and 3.3 Volume Conditioned Reconstruction 4 Experiment and 4.1 Comparison on Proxy-based and Image-based 3D Generation 4.2 Comparison on Controllable 3D Object Generation, 4.3 Interactive Generation with Part Editing & 4.4 Ablation Studies 5 Conclusions, Acknowledgments, and References SUPPLEMENTARY MATERIAL A. Implementation Details B. More Discussions C. More Experiments C MORE EXPERIMENTS C.1 Runtime Evaluation As shown in Fig. L, given a 3D proxy and text prompt, Coin3D first takes 2s to generate candidate images and 6s to generate 3Daware conditioned multiview images. During previewing, Coin3D responds to the camera rotating instantly (<0.3s) and takes 2s for convergence (baseline without volume-cache requires 6s). For interactive editing, Coin3D takes 3s to update the 2D condition and 9s to update the feature volume, which is then ready for previewing. As a comparison, existing editable 3D generation methods take much longer for feedback, e.g., ~1h for Progressive3D and FocalDreamer, ~0.5h for Fantasia3D. Finally, Coin3D takes 4~5m (600 iterations) to reconstruct and export the textured mesh (see Fig. 1 and Fig. 4 from the main paper for "proxies vs. textured meshes"). C.2 3D-Aware Controlling Strength C.3 Interactive Ed Since Fantasia3D supports fine-tuning on the pre-trained mesh, it can also conduct interactive editing by updating text prompts. Therefore, we compare our interactive editing method with Fantasia3D fine-tuning. We use the user-guided generation method mentioned in Fantasia3D. The first stage performs geometry optimization and texture optimization based on the initial shape, and the second stage uses the first stage’s optimized object but modifies the text prompt during optimization. During the experiment, we first use a flat cylinder as the initial input shape, and use text prompt “a birthday cake base” to guide the optimization. Second, we add candles by modifying the proxy shape and updating the text prompt to “a birthday cake with three candles on top” and As shown in Fig. J, our method successfully generates appealing cakes with candles, while Fantasia3D fails to achieve a reasonable result (e.g., almost no complete candle on the top). C.4 Proxy-Based 3D Generation vs. Texture Synthesis We also compare our method with texture synthesis work TEXTure [Richardson et al. 2023], which generates UV textures given the corresponding geometry. As shown in Fig. I, when given the same coarse proxy for generation, TEXTure tends to generate tightly bounded textures on the given mesh, resulting in blurry appearances and invisible facial features of the dinosaur. In contrast, our method allows a certain degree of freedom during the generation, which gracefully synthesizes the dinosaur with vivid facial details. The experiment demonstrates that the proxy-based 3D generation is far beyond the texture synthesis task, as it requires the method to generate more details upon the coarse proxy shape. C.5 Proxy-Based 3D Generation vs. Depth-Controlled 3D Generation We compare our proxy-based 3D generation with the depth-controlled 3D generation pipeline from Zero123++ [Shi et al. 2023a], where we feed the Zero123++ with the multiview depth maps rendered from the coarse shape proxy. As shown in Fig. K, even only given a coarse shape of the animal with no ears, our method still generates cute animal ears upon the simple shape, while Zero123++ can only synthesize novel views of the object that tightly fit to the coarse shape proxy with poor facial details. This demonstrates that simply using 2D depth control as a condition in multiview generation cannot achieve the ideal coarse 3D control ability like ours, which further proves the value of adding 3D-aware control in a 3D manner. C.6 User Studies of Ablation Studies We selected 10 examples of the ablation studies in Sec. 4.4 and asked 24 users to judge whether the proposed strategies improve the results. The statistic shows 78% of users believe volume-SDS improves the quality, 75% of users think 3D mask dilation makes editing more natural, 96% of users find the proxy helpful in maintaining shape integrity. C.7 User Study of 3D Interaction of Proxy-based 3D Generation We also conducted a user study of proxy-based 3D generation. We show users the process of making coarse shapes in Blender, as well as the generated multi-view images and 3D reconstruction results. We asked each participant to rate three questions: (a) the difficulty of using 3D modeling tools; (b) overall satisfaction with the effectiveness of our approach; (c) willingness to use our methods, on a scale of 1 to 5, where 1 in (a) means easy to use, 5 in (b) means satisfied with the effectiveness, and 5 in (c) means willing to use. The score of (a) is 2.38, (b) is 4.62, and (c) 4.46, which indicates that most of the participants consider the difficulty of coarse shape modeling is acceptable and are willing to use our method. Authors:
(1) Wenqi Dong, from Zhejiang University, and conducted this work during his internship at PICO, ByteDance;
(2) Bangbang Yang, from ByteDance contributed equally to this work together with Wenqi Dong;
(3) Lin Ma, ByteDance;
(4) Xiao Liu, ByteDance;
(5) Liyuan Cui, Zhejiang University;
(6) Hujun Bao, Zhejiang University;
(7) Yuewen Ma, ByteDance;
(8) Zhaopeng Cui, a Corresponding author from Zhejiang University. This paper is available on arxiv under CC BY 4.0 DEED license. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Works 2 Related Works 3 Method and 3.1 Proxy-Guided 3D Conditioning for Diffusion 3 Method and 3.1 Proxy-Guided 3D Conditioning for Diffusion 3.2 Interactive Generation Workflow and 3.3 Volume Conditioned Reconstruction 3.2 Interactive Generation Workflow and 3.3 Volume Conditioned Reconstruction 4 Experiment and 4.1 Comparison on Proxy-based and Image-based 3D Generation 4 Experiment and 4.1 Comparison on Proxy-based and Image-based 3D Generation 4.2 Comparison on Controllable 3D Object Generation, 4.3 Interactive Generation with Part Editing & 4.4 Ablation Studies 4.2 Comparison on Controllable 3D Object Generation, 4.3 Interactive Generation with Part Editing & 4.4 Ablation Studies 5 Conclusions, Acknowledgments, and References 5 Conclusions, Acknowledgments, and References SUPPLEMENTARY MATERIAL SUPPLEMENTARY MATERIAL A. Implementation Details A. Implementation Details B. More Discussions B. More Discussions C. More Experiments C. More Experiments C MORE EXPERIMENTS C.1 Runtime Evaluation As shown in Fig. L, given a 3D proxy and text prompt, Coin3D first takes 2s to generate candidate images and 6s to generate 3Daware conditioned multiview images. During previewing, Coin3D responds to the camera rotating instantly (<0.3s) and takes 2s for convergence (baseline without volume-cache requires 6s). For interactive editing, Coin3D takes 3s to update the 2D condition and 9s to update the feature volume, which is then ready for previewing. As a comparison, existing editable 3D generation methods take much longer for feedback, e.g., ~1h for Progressive3D and FocalDreamer, ~0.5h for Fantasia3D. Finally, Coin3D takes 4~5m (600 iterations) to reconstruct and export the textured mesh (see Fig. 1 and Fig. 4 from the main paper for "proxies vs. textured meshes"). C.2 3D-Aware Controlling Strength C.3 Interactive Ed Since Fantasia3D supports fine-tuning on the pre-trained mesh, it can also conduct interactive editing by updating text prompts. Therefore, we compare our interactive editing method with Fantasia3D fine-tuning. We use the user-guided generation method mentioned in Fantasia3D. The first stage performs geometry optimization and texture optimization based on the initial shape, and the second stage uses the first stage’s optimized object but modifies the text prompt during optimization. During the experiment, we first use a flat cylinder as the initial input shape, and use text prompt “a birthday cake base” to guide the optimization. Second, we add candles by modifying the proxy shape and updating the text prompt to “a birthday cake with three candles on top” and As shown in Fig. J, our method successfully generates appealing cakes with candles, while Fantasia3D fails to achieve a reasonable result (e.g., almost no complete candle on the top). C.4 Proxy-Based 3D Generation vs. Texture Synthesis We also compare our method with texture synthesis work TEXTure [Richardson et al. 2023], which generates UV textures given the corresponding geometry. As shown in Fig. I, when given the same coarse proxy for generation, TEXTure tends to generate tightly bounded textures on the given mesh, resulting in blurry appearances and invisible facial features of the dinosaur. In contrast, our method allows a certain degree of freedom during the generation, which gracefully synthesizes the dinosaur with vivid facial details. The experiment demonstrates that the proxy-based 3D generation is far beyond the texture synthesis task, as it requires the method to generate more details upon the coarse proxy shape. C.5 Proxy-Based 3D Generation vs. Depth-Controlled 3D Generation We compare our proxy-based 3D generation with the depth-controlled 3D generation pipeline from Zero123++ [Shi et al. 2023a], where we feed the Zero123++ with the multiview depth maps rendered from the coarse shape proxy. As shown in Fig. K, even only given a coarse shape of the animal with no ears, our method still generates cute animal ears upon the simple shape, while Zero123++ can only synthesize novel views of the object that tightly fit to the coarse shape proxy with poor facial details. This demonstrates that simply using 2D depth control as a condition in multiview generation cannot achieve the ideal coarse 3D control ability like ours, which further proves the value of adding 3D-aware control in a 3D manner. C.6 User Studies of Ablation Studies We selected 10 examples of the ablation studies in Sec. 4.4 and asked 24 users to judge whether the proposed strategies improve the results. The statistic shows 78% of users believe volume-SDS improves the quality, 75% of users think 3D mask dilation makes editing more natural, 96% of users find the proxy helpful in maintaining shape integrity. C.7 User Study of 3D Interaction of Proxy-based 3D Generation We also conducted a user study of proxy-based 3D generation. We show users the process of making coarse shapes in Blender, as well as the generated multi-view images and 3D reconstruction results. We asked each participant to rate three questions: (a) the difficulty of using 3D modeling tools; (b) overall satisfaction with the effectiveness of our approach; (c) willingness to use our methods, on a scale of 1 to 5, where 1 in (a) means easy to use, 5 in (b) means satisfied with the effectiveness, and 5 in (c) means willing to use. The score of (a) is 2.38, (b) is 4.62, and (c) 4.46, which indicates that most of the participants consider the difficulty of coarse shape modeling is acceptable and are willing to use our method. Authors: (1) Wenqi Dong, from Zhejiang University, and conducted this work during his internship at PICO, ByteDance; (2) Bangbang Yang, from ByteDance contributed equally to this work together with Wenqi Dong; (3) Lin Ma, ByteDance; (4) Xiao Liu, ByteDance; (5) Liyuan Cui, Zhejiang University; (6) Hujun Bao, Zhejiang University; (7) Yuewen Ma, ByteDance; (8) Zhaopeng Cui, a Corresponding author from Zhejiang University. Authors: Authors: (1) Wenqi Dong, from Zhejiang University, and conducted this work during his internship at PICO, ByteDance; (2) Bangbang Yang, from ByteDance contributed equally to this work together with Wenqi Dong; (3) Lin Ma, ByteDance; (4) Xiao Liu, ByteDance; (5) Liyuan Cui, Zhejiang University; (6) Hujun Bao, Zhejiang University; (7) Yuewen Ma, ByteDance; (8) Zhaopeng Cui, a Corresponding author from Zhejiang University. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv

Coin3D Delivers Fast, Precise 3D Generation with Strong User Approval

Table of Links Abstract and 1 Introduction 2 Related Works 3 Method and 3.1 Proxy-Guided 3D Conditioning for Diffusion 3.2 Interactive Generation Workflow and 3.3 Volume Conditioned Reconstruction 4 Experiment and 4.1 Comparison on Proxy-based and Image-based 3D Generation 4.2 Comparison on Controllable 3D Object Generation, 4.3 Interactive Generation with Part Editing & 4.4 Ablation Studies 5 Conclusions, Acknowledgments, and References SUPPLEMENTARY MATERIAL A. Implementation Details B. More Discussions C. More Experiments 4 EXPERIMENTS We first compare our method with image-based 3D generation in Sec. 4.1, and compare with controllable 3D object generation methods in Sec. 4.2. Then, we show the interactive generation applicability with designated part editing in Sec. 4.3. Finally, we perform ablation studies to analyze the design of our framework in Sec. 4.4. 4.1 Comparison on Proxy-based and Image-based 3D Generation So far, the most stable 3D object generation pipelines are mainly image-based, i.e., giving a single image as a conditioning input, and then generating multiview images for reconstruction [Liu et al. 2023a; Long et al. 2023; Shi et al. 2023a] or direct 3D representations [Hong et al. 2023]. Unlike these methods, we use a coarse shape proxy as a guidance through the entire interactive generation pipeline. Since all these methods use image conditions to bootstrap the diffusion model, we first compare our method with SOTA imagebased generation methods (i.e., Wonder3D [Long et al. 2023] and SyncDreamer [Liu et al. 2023a]) using the same image candidates, where our method also add extra coarse shapes as conditioning. Qualitative comparison. We show the multiview images and the reconstructed textured meshes in Fig. 4. As shown in Fig. 4, the predicted views and the textured meshes from Wonder3D and SyncDreamer both have some artifacts (e.g., distorted green turtle and yellow swimming ring at the first and third row in Fig. 4 (b) (c), missing hollowed handrail and short legs at the second row in Fig. 4 (b), missing white creamy middle layer at the fourth row in Fig. 4 (c)). Thanks to the proxy-guided conditioning and volume-conditioned reconstruction, our method can synthesize multiview images free of single view ambiguity by complementing 3D context from the proxy (e.g., complete chairs with correct hollowed handrail in Fig. 4 (a)), and also consistently reconstruct 3D objects with intact shape and vivid appearance. Quantitative comparison. We use CLIP score [Radford et al. 2021] to evaluate the text-object matching degree, and ImageReward [He et al. 2023; Xu et al. 2023a] and GPTEvals3D [Wu et al. 2024] to evaluate the perceptual quality of the predicted multiview images. As presented in Table 1, our method achieves the overall best metrics, demonstrating that adding proxy-based conditioning can improve the quality of 3D generation tasks. Note that Wonder3D’s ImageReward score is lower than SyncDreamer’s due to the evaluator’s bias of orthogonal image views, while their Elo scores [Elo 1967] evaluated by GPTEvals3D are comparable. User study. We also conduct a user study to compare our method with others. Following TEXTure [Richardson et al. 2023], we ask 30 users to sort 35 testing examples in random order based on the perceptual quality and content matching degree (w.r.t the given image or text prompts), and assign the scores by their ranking (i.e., with a score of 3 for the ordered best one and a score of 1 for the last one). As reported in Table 1, our method achieves the best score among all the methods. More details can be found in the supplementary material. Authors:
(1) Wenqi Dong, from Zhejiang University, and conducted this work during his internship at PICO, ByteDance;
(2) Bangbang Yang, from ByteDance contributed equally to this work together with Wenqi Dong;
(3) Lin Ma, ByteDance;
(4) Xiao Liu, ByteDance;
(5) Liyuan Cui, Zhejiang University;
(6) Hujun Bao, Zhejiang University;
(7) Yuewen Ma, ByteDance;
(8) Zhaopeng Cui, a Corresponding author from Zhejiang University. This paper is available on arxiv under CC BY 4.0 DEED license. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Works 2 Related Works 3 Method and 3.1 Proxy-Guided 3D Conditioning for Diffusion 3 Method and 3.1 Proxy-Guided 3D Conditioning for Diffusion 3.2 Interactive Generation Workflow and 3.3 Volume Conditioned Reconstruction 3.2 Interactive Generation Workflow and 3.3 Volume Conditioned Reconstruction 4 Experiment and 4.1 Comparison on Proxy-based and Image-based 3D Generation 4 Experiment and 4.1 Comparison on Proxy-based and Image-based 3D Generation 4.2 Comparison on Controllable 3D Object Generation, 4.3 Interactive Generation with Part Editing & 4.4 Ablation Studies 4.2 Comparison on Controllable 3D Object Generation, 4.3 Interactive Generation with Part Editing & 4.4 Ablation Studies 5 Conclusions, Acknowledgments, and References 5 Conclusions, Acknowledgments, and References SUPPLEMENTARY MATERIAL SUPPLEMENTARY MATERIAL A. Implementation Details A. Implementation Details B. More Discussions B. More Discussions C. More Experiments C. More Experiments 4 EXPERIMENTS We first compare our method with image-based 3D generation in Sec. 4.1, and compare with controllable 3D object generation methods in Sec. 4.2. Then, we show the interactive generation applicability with designated part editing in Sec. 4.3. Finally, we perform ablation studies to analyze the design of our framework in Sec. 4.4. 4.1 Comparison on Proxy-based and Image-based 3D Generation So far, the most stable 3D object generation pipelines are mainly image-based, i.e., giving a single image as a conditioning input, and then generating multiview images for reconstruction [Liu et al. 2023a; Long et al. 2023; Shi et al. 2023a] or direct 3D representations [Hong et al. 2023]. Unlike these methods, we use a coarse shape proxy as a guidance through the entire interactive generation pipeline. Since all these methods use image conditions to bootstrap the diffusion model, we first compare our method with SOTA imagebased generation methods (i.e., Wonder3D [Long et al. 2023] and SyncDreamer [Liu et al. 2023a]) using the same image candidates, where our method also add extra coarse shapes as conditioning. Qualitative comparison. We show the multiview images and the reconstructed textured meshes in Fig. 4. As shown in Fig. 4, the predicted views and the textured meshes from Wonder3D and SyncDreamer both have some artifacts (e.g., distorted green turtle and yellow swimming ring at the first and third row in Fig. 4 (b) (c), missing hollowed handrail and short legs at the second row in Fig. 4 (b), missing white creamy middle layer at the fourth row in Fig. 4 (c)). Thanks to the proxy-guided conditioning and volume-conditioned reconstruction, our method can synthesize multiview images free of single view ambiguity by complementing 3D context from the proxy (e.g., complete chairs with correct hollowed handrail in Fig. 4 (a)), and also consistently reconstruct 3D objects with intact shape and vivid appearance. Qualitative comparison. Quantitative comparison. We use CLIP score [Radford et al. 2021] to evaluate the text-object matching degree, and ImageReward [He et al. 2023; Xu et al. 2023a] and GPTEvals3D [Wu et al. 2024] to evaluate the perceptual quality of the predicted multiview images. As presented in Table 1, our method achieves the overall best metrics, demonstrating that adding proxy-based conditioning can improve the quality of 3D generation tasks. Note that Wonder3D’s ImageReward score is lower than SyncDreamer’s due to the evaluator’s bias of orthogonal image views, while their Elo scores [Elo 1967] evaluated by GPTEvals3D are comparable. Quantitative comparison. User study. We also conduct a user study to compare our method with others. Following TEXTure [Richardson et al. 2023], we ask 30 users to sort 35 testing examples in random order based on the perceptual quality and content matching degree (w.r.t the given image or text prompts), and assign the scores by their ranking (i.e., with a score of 3 for the ordered best one and a score of 1 for the last one). As reported in Table 1, our method achieves the best score among all the methods. More details can be found in the supplementary material. User study. Authors: (1) Wenqi Dong, from Zhejiang University, and conducted this work during his internship at PICO, ByteDance; (2) Bangbang Yang, from ByteDance contributed equally to this work together with Wenqi Dong; (3) Lin Ma, ByteDance; (4) Xiao Liu, ByteDance; (5) Liyuan Cui, Zhejiang University; (6) Hujun Bao, Zhejiang University; (7) Yuewen Ma, ByteDance; (8) Zhaopeng Cui, a Corresponding author from Zhejiang University. Authors: Authors: (1) Wenqi Dong, from Zhejiang University, and conducted this work during his internship at PICO, ByteDance; (2) Bangbang Yang, from ByteDance contributed equally to this work together with Wenqi Dong; (3) Lin Ma, ByteDance; (4) Xiao Liu, ByteDance; (5) Liyuan Cui, Zhejiang University; (6) Hujun Bao, Zhejiang University; (7) Yuewen Ma, ByteDance; (8) Zhaopeng Cui, a Corresponding author from Zhejiang University. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv

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