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A recent study conducted by Kiseki in the fall of 2024 uncovers a fascinating trend: Japanese singles are increasingly eager to connect with people from around the globe. This shift in social dynamics is noteworthy. Record Numbers of Japanese Living Abroad According to the Ministry of Foreign Affairs, a historic high of 570,000 Japanese citizens now reside overseas, the largest figure seen in over 30 years. This surge reflects a vibrant curiosity about diverse cultures, particularly among younger generations, as highlighted by Kiseki's latest research. The survey reveals that over 95% of Japanese singles are enthusiastic about engaging with foreigners. Given Japan’s historically complex attitudes toward international cultures, it’s intriguing to explore what drives this newfound openness. Understanding the Motivations Behind Japan's Singles Delving into the desires of Japanese singles is a complex endeavor. Kiseki, a part of the Social Discovery Group and recognized for its excellence in global matchmaking by the Japan Number One Research Institute LLC, conducted an insightful online survey with over 230 participants from various age brackets. The findings are compelling. A Remarkable 95% Eager to Connect with Foreigners One of the most striking insights from Kiseki’s 2024 survey is that an impressive 95% of respondents express a desire to connect with individuals from other countries. The enthusiasm is nearly equal among men (96%) and women (94%), indicating that this interest transcends gender. Many participants articulated their intentions clearly: while some are in search of love and romance, a significant number prioritize friendship. In fact, 70% are looking to forge friendships through communication, while 29% simply wish for someone to converse with. Language acquisition also plays a crucial role, with 56% eager to practice their speaking skills with others.While friendship and language learning are primary motivators, romance remains an appealing prospect for many. Kiseki reports that 21% of respondents are actively seeking love, with men showing slightly more interest than women. The Rise of International Romance The trend toward international relationships is already gaining momentum in Japan. The survey indicates that 45% of participants have engaged in romantic relationships with foreigners, with women (50%) reporting higher rates than men (36%). Digital platforms are pivotal in fostering these international connections. Kiseki's findings show that 32% have met foreigners online, and 11% have established both online and offline relationships. Younger individuals are particularly inclined to connect digitally, although offline interactions tend to increase with age. When asked about their preferred methods for meeting new people in the future, over 70% expressed a willingness to engage through online platforms or dating sites. Notably, many Japanese singles prefer a gradual approach—favoring casual friendships and language exchanges before diving into romantic pursuits. Kiseki: Bridging Connections Across Borders While there’s a clear enthusiasm among Japanese singles for meeting foreigners, navigating these connections can be challenging. Launched by SDG, Kiseki has become a leading platform for connecting individuals from approximately 80 countries. Kiseki offers seamless communication features such as AI-assisted chat translations, speed matching, and video calls, facilitating meaningful interactions across borders. The platform encourages users to take their time in building friendships and developing online relationships while also serving as a resource for language learning and cultural exploration. Safety is paramount; Kiseki employs rigorous identity and age verification through trusted providers like Liquid, ensuring a secure environment for its users. In conclusion, as Japan’s singles increasingly seek connections beyond their borders, platforms like Kiseki play a vital role in fostering these exciting new relationships—whether they blossom into friendships or romantic partnerships. A recent study conducted by Kiseki in the fall of 2024 uncovers a fascinating trend: Japanese singles are increasingly eager to connect with people from around the globe. This shift in social dynamics is noteworthy. Kiseki Record Numbers of Japanese Living Abroad According to the Ministry of Foreign Affairs, a historic high of 570,000 Japanese citizens now reside overseas, the largest figure seen in over 30 years. This surge reflects a vibrant curiosity about diverse cultures, particularly among younger generations, as highlighted by Kiseki's latest research. The survey reveals that over 95% of Japanese singles are enthusiastic about engaging with foreigners. Given Japan’s historically complex attitudes toward international cultures, it’s intriguing to explore what drives this newfound openness. Understanding the Motivations Behind Japan's Singles Delving into the desires of Japanese singles is a complex endeavor. Kiseki, a part of the Social Discovery Group and recognized for its excellence in global matchmaking by the Japan Number One Research Institute LLC, conducted an insightful online survey with over 230 participants from various age brackets. The findings are compelling. Social Discovery Group A Remarkable 95% Eager to Connect with Foreigners One of the most striking insights from Kiseki’s 2024 survey is that an impressive 95% of respondents express a desire to connect with individuals from other countries. The enthusiasm is nearly equal among men (96%) and women (94%), indicating that this interest transcends gender. Many participants articulated their intentions clearly: while some are in search of love and romance, a significant number prioritize friendship. In fact, 70% are looking to forge friendships through communication, while 29% simply wish for someone to converse with. Language acquisition also plays a crucial role, with 56% eager to practice their speaking skills with others.While friendship and language learning are primary motivators, romance remains an appealing prospect for many. Many participants articulated their intentions clearly: while some are in search of love and romance, a significant number prioritize friendship. In fact, 70% are looking to forge friendships through communication, while 29% simply wish for someone to converse with. Language acquisition also plays a crucial role, with 56% eager to practice their speaking skills with others.While friendship and language learning are primary motivators, romance remains an appealing prospect for many. Kiseki reports that 21% of respondents are actively seeking love, with men showing slightly more interest than women. The Rise of International Romance The trend toward international relationships is already gaining momentum in Japan. The survey indicates that 45% of participants have engaged in romantic relationships with foreigners, with women (50%) reporting higher rates than men (36%). Digital platforms are pivotal in fostering these international connections. Kiseki's findings show that 32% have met foreigners online, and 11% have established both online and offline relationships. Younger individuals are particularly inclined to connect digitally, although offline interactions tend to increase with age. When asked about their preferred methods for meeting new people in the future, over 70% expressed a willingness to engage through online platforms or dating sites . Notably, many Japanese singles prefer a gradual approach—favoring casual friendships and language exchanges before diving into romantic pursuits. dating sites Kiseki: Bridging Connections Across Borders While there’s a clear enthusiasm among Japanese singles for meeting foreigners, navigating these connections can be challenging. Launched by SDG , Kiseki has become a leading platform for connecting individuals from approximately 80 countries. Kiseki offers seamless communication features such as AI-assisted chat translations, speed matching, and video calls, facilitating meaningful interactions across borders. The platform encourages users to take their time in building friendships and developing online relationships while also serving as a resource for language learning and cultural exploration. Safety is paramount; Kiseki employs rigorous identity and age verification through trusted providers like Liquid, ensuring a secure environment for its users. SDG In conclusion, as Japan’s singles increasingly seek connections beyond their borders, platforms like Kiseki play a vital role in fostering these exciting new relationships—whether they blossom into friendships or romantic partnerships. In conclusion, as Japan’s singles increasingly seek connections beyond their borders, platforms like Kiseki play a vital role in fostering these exciting new relationships—whether they blossom into friendships or romantic partnerships.

Global Romance Gains Popularity in Japan, Reveals 2024 Survey by Kiseki

Wêreldwye romanse wen gewildheid in Japan, onthul 2024-opname deur Kiseki

Global Romance získává popularitu v Japonsku, odhaluje 2024 průzkum od Kiseki

El romance global gana popularidad en Japón, según una encuesta de Kiseki para 2024

Globalna romantika postaje sve popularnija u Japanu, otkriva Kisekijevo istraživanje iz 2024

Համաշխարհային սիրավեպը ժողովրդականություն է ձեռք բերում Ճապոնիայում, բացահայտում է 2024 թվականի հետազոտությունը Կիսեկիի կողմից

キセキの2024年調査によると、日本でグローバルロマンスの人気が高まっていることが明らかになった。

Global Romance ទទួលបានប្រជាប្រិយភាពនៅក្នុងប្រទេសជប៉ុន បង្ហាញការស្ទង់មតិឆ្នាំ 2024 ដោយ Kiseki

Pasaulinis romanas populiarėja Japonijoje, atskleidžia 2024 m. Kiseki apklausa

Global Romance Yamamaye mu Buyapani, Yerekana 2024 Ubushakashatsi bwakozwe na Kiseki

க்ளோபல் ரொமான்ஸ் ஜப்பானில் பிரபலமாகிறது, கிசெகியின் 2024 கணக்கெடுப்பை வெளிப்படுத்துகிறது

ዓለማዊ ፍቕራዊ ርክብ ኣብ ጃፓን ተፈታውነት ረኺቡ፡ ኣብ 2024 ብኪሰኪ ዝተገብረ መጽናዕቲ ኣቃሊዑ

Kiseki'nin 2024 Anketi, Küresel Romantizmin Japonya'da Popülerlik Kazandığını Açıkladı

Hotshot is an online multi-player shooter game where players can make money by shooting each other in the game. Each time a player is shot in the game, in-game tokens are transferred from the balance/score of the play that was shot to the shooter’s balance/score. Fast transaction gaming (FTG) is a new form of play-to-earn (P2E) gaming involving rapid transactions between players. Player-to-player transactions are based on game events – such as a player being shot by another player. Hotshot’s first Alpha Play Day will be in November 2024 and will be announced imminently. Players can already register for the Alpha Play Day at https://www.hot-shot.io/ Hotshot is an online multi-player game of skill where each player can shoot other players to earn in-game tokens from them. Each time a player is shot in the game, tokens are transferred from the balance/score of the player that was shot to the shooter’s balance/score. Players can sign into the game by email or by signing in with their blockchain wallet.  To play Hotshot, players need to purchase in-game tokens, with each token representing the right to play. Players can purchase in-game tokens in standard amounts of USD $10, USD $20 and USD $50. In-game tokens can be purchased either by credit or debit card, or, by making a crypto asset transfer. Rapidfire plans to accept crypto asset payments on Ethereum, Polygon, Optimism, Arbitrum and Tron blockchains with the following tokens / base currencies ETH, USDT, USDC, MATIC, TRX, SHIB, LINK, OMG, DAI, BAT, UNI, MANA, SAND, AAVE, PEPE, GRT, APE, CHZ, SUSHI, FTM, 1INCH, STORJ, WBTC, IMX, ARB, OP, LPT. In Hotshot, players enter one of five playground maps to battle against up to 40 players in total. The battle begins - when a player shoots another player, the hit value of, for example, $1 is transferred from the shot player's balance to the shooter player's balance. Rapidfire Unicorn's patented Fast Transaction Gaming (FTG) systems enable new types of Play-to-Earn gaming with high earning potential for skilled gamers. Each available Game playground has an advertised hit value of either $1, $2 or $5 worth of in-game tokens. Players can take out their winnings, by redeeming their in-game ‘tokens’ for funds and withdrawing such funds from the Game to the credit/debit card or blockchain wallet used initially to purchase in-game tokens and the right to play. Hotshot can be played in any modern Web browser, both on PCs and on mobile devices. Hotshot will be available in most countries of the World. A spokesperson for Rapidfire Unicorn commented: "This is the advent of GigE Gaming. Fast Transaction Gaming (FTG) brings a new economic dimension to gaming. We cannot wait to see the reaction of gamers when they get to try Hotshot this November!" The first Alpha Play Day will be held in November. The actual date will be announced soon on Hotshot's social media channels. On Alpha Play Day, the first 300 players to play Hotshot will receive USD $20 worth of in-game tokens for free. Hotshot in-game tokens are redeemable for real cash or cryptocurrencies. Follow news about Hotshot on these social media channels: X: https://x.com/PlayHotshot Facebook: https://www.facebook.com/profile.php?id=61566622851528 Instagram: https://www.instagram.com/playhotshotgame TikTok: https://www.tiktok.com/@playhotshot Twitch: https://www.twitch.tv/playhotshot YouTube: https://www.youtube.com/@PlayHotshot Telegram: t.me/playhotshot LinkedIn: https://www.linkedin.com/company/rfuni/ Rapidfire Unicorn Web Site: https://www.rfuni.com/ Hotshot Game Web Site: https://www.hot-shot.io/ For further information please contact the Rapidfire Unicorn Press Office at https://www.rfuni.com/ About Rapidfire Unicorn Ltd. Rapidfire Unicorn Ltd. is a London-based games studio that develops games, gaming technology and intellectual property focused on fast transaction gaming (FTG). The team behind Rapidfire Unicorn spans from 1980s microcomputer game veterans through to modern online games designers that have been responsible for producing over 40 past games titles. This article is published under HackerNoon Business Blogging program. Do your own research before making any financial decisions. Hotshot is an online multi-player shooter game where players can make money by shooting each other in the game. Each time a player is shot in the game, in-game tokens are transferred from the balance/score of the play that was shot to the shooter’s balance/score. Fast transaction gaming (FTG) is a new form of play-to-earn (P2E) gaming involving rapid transactions between players. Player-to-player transactions are based on game events – such as a player being shot by another player. Hotshot’s first Alpha Play Day will be in November 2024 and will be announced imminently. Players can already register for the Alpha Play Day at https://www.hot-shot.io/ https://www.hot-shot.io/ https://www.hot-shot.io/ Hotshot is an online multi-player game of skill where each player can shoot other players to earn in-game tokens from them. Each time a player is shot in the game, tokens are transferred from the balance/score of the player that was shot to the shooter’s balance/score. Players can sign into the game by email or by signing in with their blockchain wallet.  To play Hotshot, players need to purchase in-game tokens, with each token representing the right to play. Players can purchase in-game tokens in standard amounts of USD $10, USD $20 and USD $50. In-game tokens can be purchased either by credit or debit card, or, by making a crypto asset transfer. Rapidfire plans to accept crypto asset payments on Ethereum, Polygon, Optimism, Arbitrum and Tron blockchains with the following tokens / base currencies ETH, USDT, USDC, MATIC, TRX, SHIB, LINK, OMG, DAI, BAT, UNI, MANA, SAND, AAVE, PEPE, GRT, APE, CHZ, SUSHI, FTM, 1INCH, STORJ, WBTC, IMX, ARB, OP, LPT. In Hotshot, players enter one of five playground maps to battle against up to 40 players in total. The battle begins - when a player shoots another player, the hit value of, for example, $1 is transferred from the shot player's balance to the shooter player's balance. Rapidfire Unicorn's patented Fast Transaction Gaming (FTG) systems enable new types of Play-to-Earn gaming with high earning potential for skilled gamers. Each available Game playground has an advertised hit value of either $1, $2 or $5 worth of in-game tokens. Players can take out their winnings, by redeeming their in-game ‘tokens’ for funds and withdrawing such funds from the Game to the credit/debit card or blockchain wallet used initially to purchase in-game tokens and the right to play. Hotshot can be played in any modern Web browser, both on PCs and on mobile devices. Hotshot will be available in most countries of the World. A spokesperson for Rapidfire Unicorn commented: "This is the advent of GigE Gaming. Fast Transaction Gaming (FTG) brings a new economic dimension to gaming. We cannot wait to see the reaction of gamers when they get to try Hotshot this November!" "This is the advent of GigE Gaming. Fast Transaction Gaming (FTG) brings a new economic dimension to gaming. We cannot wait to see the reaction of gamers when they get to try Hotshot this November!" The first Alpha Play Day will be held in November. The actual date will be announced soon on Hotshot's social media channels. On Alpha Play Day, the first 300 players to play Hotshot will receive USD $20 worth of in-game tokens for free. Hotshot in-game tokens are redeemable for real cash or cryptocurrencies. Follow news about Hotshot on these social media channels: Follow news about Hotshot on these social media channels: X: https://x.com/PlayHotshot https://x.com/PlayHotshot https://x.com/PlayHotshot Facebook: https://www.facebook.com/profile.php?id=61566622851528 https://www.facebook.com/profile.php?id=61566622851528 https://www.facebook.com/profile.php?id=61566622851528 Instagram: https://www.instagram.com/playhotshotgame https://www.instagram.com/playhotshotgame https://www.instagram.com/playhotshotgame TikTok: https://www.tiktok.com/@playhotshot https://www.tiktok.com/@playhotshot https://www.tiktok.com/@playhotshot Twitch: https://www.twitch.tv/playhotshot https://www.twitch.tv/playhotshot https://www.twitch.tv/playhotshot YouTube: https://www.youtube.com/@PlayHotshot https://www.youtube.com/@PlayHotshot https://www.youtube.com/@PlayHotshot Telegram: t.me/playhotshot t.me/playhotshot t.me/playhotshot LinkedIn: https://www.linkedin.com/company/rfuni/ https://www.linkedin.com/company/rfuni/ https://www.linkedin.com/company/rfuni/ Rapidfire Unicorn Web Site: https://www.rfuni.com/ https://www.rfuni.com/ https://www.rfuni.com/ Hotshot Game Web Site: https://www.hot-shot.io/ https://www.hot-shot.io/ https://www.hot-shot.io/ For further information please contact the Rapidfire Unicorn Press Office at https://www.rfuni.com/ For further information please contact the Rapidfire Unicorn Press Office at https://www.rfuni.com/ https://www.rfuni.com/ https://www.rfuni.com/ About Rapidfire Unicorn Ltd. About Rapidfire Unicorn Ltd. Rapidfire Unicorn Ltd. is a London-based games studio that develops games, gaming technology and intellectual property focused on fast transaction gaming (FTG). The team behind Rapidfire Unicorn spans from 1980s microcomputer game veterans through to modern online games designers that have been responsible for producing over 40 past games titles. This article is published under HackerNoon Business Blogging program. Do your own research before making any financial decisions. This article is published under HackerNoon Business Blogging program. Do your own research before making any financial decisions. Business Blogging Business Blogging

Rapidfire Unicorn reveals “Hotshot” Shoot-to-Earn PVP Game at GamesBeat NEXT Industry Event

Rapidfire Unicorn GamesBeat NEXT Industry Event-də “Hotshot” Shoot-to-Earn PVP Oyununu nümayiş etdirir

Rapidfire Unicorn revela el juego PvP de disparos para ganar “Hotshot” en el evento de la industria GamesBeat NEXT

Rapidfire Unicorn بازی «Hotshot» Shoot-to-Earn PVP را در رویداد صنعت GamesBeat NEXT معرفی کرد.

Rapidfire Unicorn revela o xogo PVP Shoot-to-Earn "Hotshot" no NEXT Industry Event de GamesBeat

Rapidfire Unicorn が GamesBeat NEXT 業界イベントで Shoot-to-Earn PVP ゲーム「Hotshot」を発表

Rapidfire Unicorn ເປີດເຜີຍ "Hotshot" ເກມຍິງເພື່ອຫາລາຍໄດ້ PVP ຢູ່ GamesBeat ເຫດການອຸດສາຫະກໍາຕໍ່ໄປ

Rapidfire Unicorn dia manambara ny lalao PVP Shoot-to-Earn "Hotshot" ao amin'ny GamesBeat NEXT Industry Event

Rapidfire Unicorn ujawnia grę PVP „Hotshot” Shoot-to-Earn na GamesBeat NEXT Industry Event

د ریپډ فایر یونیکورن د "هاټ شاټ" شوټ څخه ترلاسه کولو PVP لوبه په GamesBeat NEXT Industry Event کې ښکاره کوي

Rapidfire Unicorn zbulon lojën "Hotshot" Shoot-to-Earn PVP në GamesBeat NEXT Industry Event

Rapidfire Unicorn yi paluxa Ntlangu wa PVP wa “Hotshot” wo Duvula ku Hola eka GamesBeat NEXT Industry Event

Rapidfire Unicorn GamesBeat NEXT Industry Event-da "Hotshot" Shoot-to-Earn PVP o'yinini namoyish etadi.

Table of Links Abstract and 1. Introduction 2 Architectural details and 2.1 Sparse Mixture of Experts 3 Results 3.1 Multilingual benchmarks, 3.2 Long range performance, and 3.3 Bias Benchmarks 4 Instruction Fine-tuning 5 Routing analysis 6 Conclusion, Acknowledgements, and References 5 Routing analysis In this section, we perform a small analysis on the expert selection by the router. In particular, we are interested to see if during training some experts specialized to some specific domains (e.g. mathematics, biology, philosophy, etc.). To investigate this, we measure the distribution of selected experts on different subsets of The Pile validation dataset [14]. Results are presented in Figure 7, for layers 0, 15, and 31 (layers 0 and 31 respectively being the first and the last layers of the model). Surprisingly, we do not observe obvious patterns in the assignment of experts based on the topic. For instance, at all layers, the distribution of expert assignment is very similar for ArXiv papers (written in Latex), for biology (PubMed Abstracts), and for Philosophy (PhilPapers) documents. Only for DM Mathematics we note a marginally different distribution of experts. This divergence is likely a consequence of the dataset’s synthetic nature and its limited coverage of the natural language spectrum, and is particularly noticeable at the first and last layers, where the hidden states are very correlated to the input and output embeddings respectively. This suggests that the router does exhibit some structured syntactic behavior. Figure 8 shows examples of text from different domains (Python code, mathematics, and English), where each token is highlighted with a background color corresponding to its selected expert. The figure shows that words such as ‘self’ in Python and ‘Question’ in English often get routed through the same expert even though they involve multiple tokens. Similarly, in code, the indentation tokens are always assigned to the same experts, particularly at the first and last layers where the hidden states are more correlated to the input and output of the model. We also note from Figure 8 that consecutive tokens are often assigned the same experts. In fact, we observe some degree of positional locality in The Pile datasets. Table 5 shows the proportion of consecutive tokens that get the same expert assignments per domain and layer. The proportion of repeated consecutive assignments is significantly higher than random for higher layers. This has implications in how one might optimize the model for fast training and inference. For example, cases with high locality are more likely to cause over-subscription of certain experts when doing Expert Parallelism. Conversely, this locality can be leveraged for caching, as is done in [11]. A more complete view of these same expert frequency is provided for all layers and across datasets in Figure 10 in the Appendix. This paper is available on arxiv under CC 4.0 license. Authors:
(1) Albert Q. Jiang;
(2) Alexandre Sablayrolles;
(3) Antoine Roux;
(4) Arthur Mensch;
(5) Blanche Savary;
(6) Chris Bamford;
(7) Devendra Singh Chaplot;
(8) Diego de las Casas;
(9) Emma Bou Hanna;
(10) Florian Bressand;
(11) Gianna Lengyel;
(12) Guillaume Bour;
(13) Guillaume Lample;
(14) Lélio Renard Lavaud;
(15) Lucile Saulnier;
(16) Marie-Anne Lachaux;
(17) Pierre Stock;
(18) Sandeep Subramanian;
(19) Sophia Yang;
(20) Szymon Antoniak;
(21) Teven Le Scao;
(22) Théophile Gervet;
(23) Thibaut Lavril;
(24) Thomas Wang;
(25) Timothée Lacroix;
(26) William El Sayed. Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 Architectural details and 2.1 Sparse Mixture of Experts 2 Architectural details and 2.1 Sparse Mixture of Experts 3 Results 3 Results 3.1 Multilingual benchmarks, 3.2 Long range performance, and 3.3 Bias Benchmarks 3.1 Multilingual benchmarks, 3.2 Long range performance, and 3.3 Bias Benchmarks 4 Instruction Fine-tuning 4 Instruction Fine-tuning 5 Routing analysis 5 Routing analysis 6 Conclusion, Acknowledgements, and References 6 Conclusion, Acknowledgements, and References 5 Routing analysis In this section, we perform a small analysis on the expert selection by the router. In particular, we are interested to see if during training some experts specialized to some specific domains (e.g. mathematics, biology, philosophy, etc.). To investigate this, we measure the distribution of selected experts on different subsets of The Pile validation dataset [14]. Results are presented in Figure 7, for layers 0, 15, and 31 (layers 0 and 31 respectively being the first and the last layers of the model). Surprisingly, we do not observe obvious patterns in the assignment of experts based on the topic. For instance, at all layers, the distribution of expert assignment is very similar for ArXiv papers (written in Latex), for biology (PubMed Abstracts), and for Philosophy (PhilPapers) documents. Only for DM Mathematics we note a marginally different distribution of experts. This divergence is likely a consequence of the dataset’s synthetic nature and its limited coverage of the natural language spectrum, and is particularly noticeable at the first and last layers, where the hidden states are very correlated to the input and output embeddings respectively. This suggests that the router does exhibit some structured syntactic behavior. Figure 8 shows examples of text from different domains (Python code, mathematics, and English), where each token is highlighted with a background color corresponding to its selected expert. The figure shows that words such as ‘self’ in Python and ‘Question’ in English often get routed through the same expert even though they involve multiple tokens. Similarly, in code, the indentation tokens are always assigned to the same experts, particularly at the first and last layers where the hidden states are more correlated to the input and output of the model. We also note from Figure 8 that consecutive tokens are often assigned the same experts. In fact, we observe some degree of positional locality in The Pile datasets. Table 5 shows the proportion of consecutive tokens that get the same expert assignments per domain and layer. The proportion of repeated consecutive assignments is significantly higher than random for higher layers. This has implications in how one might optimize the model for fast training and inference. For example, cases with high locality are more likely to cause over-subscription of certain experts when doing Expert Parallelism. Conversely, this locality can be leveraged for caching, as is done in [11]. A more complete view of these same expert frequency is provided for all layers and across datasets in Figure 10 in the Appendix. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv Authors: (1) Albert Q. Jiang; (2) Alexandre Sablayrolles; (3) Antoine Roux; (4) Arthur Mensch; (5) Blanche Savary; (6) Chris Bamford; (7) Devendra Singh Chaplot; (8) Diego de las Casas; (9) Emma Bou Hanna; (10) Florian Bressand; (11) Gianna Lengyel; (12) Guillaume Bour; (13) Guillaume Lample; (14) Lélio Renard Lavaud; (15) Lucile Saulnier; (16) Marie-Anne Lachaux; (17) Pierre Stock; (18) Sandeep Subramanian; (19) Sophia Yang; (20) Szymon Antoniak; (21) Teven Le Scao; (22) Théophile Gervet; (23) Thibaut Lavril; (24) Thomas Wang; (25) Timothée Lacroix; (26) William El Sayed. Authors: Authors: (1) Albert Q. Jiang; (2) Alexandre Sablayrolles; (3) Antoine Roux; (4) Arthur Mensch; (5) Blanche Savary; (6) Chris Bamford; (7) Devendra Singh Chaplot; (8) Diego de las Casas; (9) Emma Bou Hanna; (10) Florian Bressand; (11) Gianna Lengyel; (12) Guillaume Bour; (13) Guillaume Lample; (14) Lélio Renard Lavaud; (15) Lucile Saulnier; (16) Marie-Anne Lachaux; (17) Pierre Stock; (18) Sandeep Subramanian; (19) Sophia Yang; (20) Szymon Antoniak; (21) Teven Le Scao; (22) Théophile Gervet; (23) Thibaut Lavril; (24) Thomas Wang; (25) Timothée Lacroix; (26) William El Sayed.

Routing Analysis Reveals Expert Selection Patterns in Mixtral

PALO ALTO, California, October 16th, 2024/GamingWire/--Tales—the popular AI gaming project spearheaded by a team of Stanford PhDs and Game developers—has today announced its innovative debut product: a Large World Model (LWM) that can generate entire digital worlds using simple text-to-game prompts. Tales intends to completely transform the world of gaming by enabling users to create fully functional games without the need for any development or game design experience. The aim is to empower players to overthrow the gaming establishment. https://www.youtube.com/embed/_CUoVGW8VCw Video: https://www.youtube.com/watch?v=_CUoVGW8VCw Competing with the world’s leading studios, Tales allows gamers to ‘bring this vision to life’ by creating user-generated, interactive, and immersive experiences. By crowdsourcing data, resources, and infrastructure, Tales is developing Sia, perhaps the most radical AI model to-date. Building Games in Seconds With a Text Prompt Similar to how chatbots like ChatGPT and Claude are powered by Large Language Models (LLMs), which specialize in processing and generating text-based outputs, Tales is building its own Large World Model designed for video game creation. This LWM is capable of understanding and generating all components of a video game— from environments, physics, 3D models, and gameplay footage to NPC (non-player character) behavior—along with detailed metadata. While an LLM learns language patterns by training on vast amounts of text, an LWM trains on gameplay data, video content, 3D assets, descriptive metadata, and feedback over time. This enables the LWM to understand how games are structured, refining its ability to create complex game elements and mechanics. Tales can output fully functional games by leveraging 3D engines, spatial reasoning algorithms, and NPC behavior systems. With just a simple text prompt like, “make a first person shooter in space” the LWM can generate the requested game, which is customizable and immediately playable. The model essentially serves as a tool for procedurally generating games in real-time and marks a substantial evolution from existing AI offerings. Tales' outputs extend beyond games, with possibilities for virtual reality worlds, interactive experiences, and immersive educational tools, making this a diversified value proposition for potential future investors. “Tales truly feels like something out of a sci-fi film, and we can’t wait to make it a reality,” said Jason Krupat, Head of Product.“The gaming industry is in desperate need of a revolution, and putting the power to create in the hands of gamers could be the start of a new era of entertainment that extends far beyond games. A lack of resources should never get in the way of a creative spark, and empowering creators in this way means so much to us.” How does Tales learn? In one of the most ambitious crowdsourced projects in history, Tales utilizes data, storage, and computational power to train its Large World Model. To ensure the community are engaged and incentivized to build this together, Tales is launching a rewards-based incentive system. Users can submit anything from gameplay footage, in-game assets, and extensive environment descriptions to form a fully transparent dataset, which is tracked and documented to ensure provenance and preserve privacy. “The systems of the future place increasingly stringent demands on infrastructure and data, posing unique challenges in the creation of a project like Tales—and this calls for unique solutions,” said Viktor Uzunov, Head of Community.“This is why we’ve decided to bootstrap the power of what could be one of the fastest-growing communities in tech. Why can’t we take on the largest competitors in the industry by working together with gamers?” Tales will be ready for early access in November. For more information, please visit https://tales.world/. About Tales Tales is an ambitious next-generation gaming platform, powered by AI. Tales is pioneering crowdsourced generative AI within the gaming industry with its large world model. By crowdsourcing vast amounts of data and computational power, the team including Stanford PhDs and Game Developers based out of Palo Alto, are building one of the world’s most powerful AI models ever, democratizing game creation and empowering creators to bring their vision to life with zero friction. To follow on social media: X, Telegram, Discord, TikTok, Twitch, Medium, YouTube Contact Head of Community Viktor Uzunov Tales pr@tales.world This story was distributed as a release by Gamingwire under HackerNoon’s Business Blogging Program. Learn more about the program here. PALO ALTO, California, October 16th, 2024/GamingWire/--Tales —the popular AI gaming project spearheaded by a team of Stanford PhDs and Game developers—has today announced its innovative debut product: a Large World Model (LWM) that can generate entire digital worlds using simple text-to-game prompts. PALO ALTO, California, October 16th, 2024/GamingWire/--Tales Tales intends to completely transform the world of gaming by enabling users to create fully functional games without the need for any development or game design experience. The aim is to empower players to overthrow the gaming establishment . overthrow the gaming establishment overthrow the gaming establishment https://www.youtube.com/embed/_CUoVGW8VCw https://www.youtube.com/embed/_CUoVGW8VCw https://www.youtube.com/embed/_CUoVGW8VCw Video: https://www.youtube.com/watch?v=_CUoVGW8VCw Competing with the world’s leading studios, Tales allows gamers to ‘ bring this vision to life ’ by creating user-generated, interactive, and immersive experiences. By crowdsourcing data, resources, and infrastructure, Tales is developing Sia, perhaps the most radical AI model to-date. bring this vision to life bring this vision to life Building Games in Seconds With a Text Prompt Similar to how chatbots like ChatGPT and Claude are powered by Large Language Models (LLMs), which specialize in processing and generating text-based outputs, Tales is building its own Large World Model designed for video game creation. This LWM is capable of understanding and generating all components of a video game— from environments, physics, 3D models, and gameplay footage to NPC (non-player character) behavior—along with detailed metadata. While an LLM learns language patterns by training on vast amounts of text, an LWM trains on gameplay data, video content, 3D assets, descriptive metadata, and feedback over time. This enables the LWM to understand how games are structured, refining its ability to create complex game elements and mechanics. Tales can output fully functional games by leveraging 3D engines, spatial reasoning algorithms, and NPC behavior systems. With just a simple text prompt like, “make a first person shooter in space” the LWM can generate the requested game, which is customizable and immediately playable. The model essentially serves as a tool for procedurally generating games in real-time and marks a substantial evolution from existing AI offerings. Tales' outputs extend beyond games, with possibilities for virtual reality worlds, interactive experiences, and immersive educational tools, making this a diversified value proposition for potential future investors. “Tales truly feels like something out of a sci-fi film, and we can’t wait to make it a reality,” said Jason Krupat, Head of Product.“The gaming industry is in desperate need of a revolution, and putting the power to create in the hands of gamers could be the start of a new era of entertainment that extends far beyond games. A lack of resources should never get in the way of a creative spark, and empowering creators in this way means so much to us.” “Tales truly feels like something out of a sci-fi film, and we can’t wait to make it a reality,” said Jason Krupat, Head of Product.“The gaming industry is in desperate need of a revolution, and putting the power to create in the hands of gamers could be the start of a new era of entertainment that extends far beyond games. A lack of resources should never get in the way of a creative spark, and empowering creators in this way means so much to us.” How does Tales learn? In one of the most ambitious crowdsourced projects in history, Tales utilizes data, storage, and computational power to train its Large World Model. To ensure the community are engaged and incentivized to build this together, Tales is launching a rewards-based incentive system. Users can submit anything from gameplay footage, in-game assets, and extensive environment descriptions to form a fully transparent dataset, which is tracked and documented to ensure provenance and preserve privacy. “The systems of the future place increasingly stringent demands on infrastructure and data, posing unique challenges in the creation of a project like Tales—and this calls for unique solutions,” said Viktor Uzunov, Head of Community.“This is why we’ve decided to bootstrap the power of what could be one of the fastest-growing communities in tech. Why can’t we take on the largest competitors in the industry by working together with gamers?” “The systems of the future place increasingly stringent demands on infrastructure and data, posing unique challenges in the creation of a project like Tales—and this calls for unique solutions,” said Viktor Uzunov, Head of Community.“This is why we’ve decided to bootstrap the power of what could be one of the fastest-growing communities in tech. Why can’t we take on the largest competitors in the industry by working together with gamers?” Tales will be ready for early access in November. For more information, please visit https://tales.world/ . https://tales.world/ https://tales.world/ About Tales Tales is an ambitious next-generation gaming platform, powered by AI. Tales is pioneering crowdsourced generative AI within the gaming industry with its large world model. By crowdsourcing vast amounts of data and computational power, the team including Stanford PhDs and Game Developers based out of Palo Alto, are building one of the world’s most powerful AI models ever, democratizing game creation and empowering creators to bring their vision to life with zero friction. To follow on social media: X , Telegram , Discord , TikTok , Twitch , Medium , YouTube X X Telegram Telegram Discord Discord TikTok TikTok Twitch Twitch Medium Medium YouTube YouTube Contact Head of Community Viktor Uzunov Tales pr@tales.world This story was distributed as a release by Gamingwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Gamingwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Tales Reveals Gaming AI: Enables Users To Build And Play Any Game

Tales Reveals Gaming AI: stel gebruikers in staat om enige speletjie te bou en te speel

Tales revela inteligencia artificial para juegos: permite a los usuarios crear y jugar cualquier juego

Tales Reveals Gaming AI: Lehetővé teszi a felhasználók számára, hogy bármilyen játékot építsenek és játszanak

Tales Reveals Gaming AI: מאפשר למשתמשים לבנות ולשחק כל משחק

テイルズがゲームAIを発表: ユーザーがあらゆるゲームを構築してプレイできるようにする

Tales បង្ហាញ Gaming AI៖ អនុញ្ញាតឱ្យអ្នកប្រើប្រាស់បង្កើត និងលេងហ្គេមណាមួយ។

Tales Gaming AI'ти ачып берет: Колдонуучуларга каалаган оюнду курууга жана ойноого мүмкүнчүлүк берет

Tales тоглоомын хиймэл оюун ухааныг илчиллээ: Хэрэглэгчдэд ямар ч тоглоом бүтээх, тоглох боломжийг олгодог

Tales Reveals Gaming AI: प्रयोगकर्ताहरूलाई कुनै पनि खेल बनाउन र खेल्न सक्षम बनाउँछ

Талес Ревеалс Гаминг АИ: Омогућава корисницима да направе и играју било коју игру

Афсонаҳои бозӣ AI-ро ошкор мекунанд: ба корбарон имкон медиҳад, ки ҳама гуна бозиро созанд ва бозӣ кунанд

Iintsomi zityhila umdlalo we-AI: Ivumela abasebenzisi ukuba bakhe kwaye badlale nawuphi na umdlalo

In December 2023, it was discovered that an NPM package commonly used by decentralized web applications (dApps) had been compromised. The package in question, @ledgerhq/connect-kit, is maintained by Ledger, a well-known and arguably the most trusted provider of secure hardware wallets. Ironic right? Well, not really, because the compromised package has nothing to do with the ledger's secure hardware wallets. However, the incident understandably raised concerns among users about the security of their assets, despite those assets being stored offline in hardware wallets. While the compromised package posed no immediate threat to Ledger's hardware devices, the situation sparked widespread discussion and speculation. The prevailing theory suggests that the compromise occurred due to a vulnerability in Ledger’s GitHub workflow. It is believed that an attacker exploited a GitHub pull request workflow to gain access to Ledger's NPM keys, enabling them to publish malicious code. The malicious update reportedly caused a secondary window to open when users attempted to connect their wallets. The Experiment The incident piqued my curiosity, prompting me to question whether GitHub workflows were inherently flawed or if there was more nuance to the exploit. To explore this, I conducted an experiment to see if I could replicate the vulnerability. Using an existing open-source repository, I attempted to recreate the exploit. During my testing, I discovered that: 1. A pull request can edit a workflow and the new workflow will run immediately after the pull request is made The screenshot below displays the contents of a pipeline.yml file from the repository I was working with. The pipeline is configured to trigger every push to the main branch, deploying the serverless application to AWS. I proceeded by creating a new branch within the repository and modifying the pipeline file. The updated configuration was set to trigger the workflow on every pull request, regardless of the branch. The screenshot below illustrates the modified state of the file. Along with these modifications, I added an instruction to print the AWS_REGION GitHub secret, which was already present in the repository. I expected to see the value displayed in the workflow logs after the action was executed successfully. I then submitted a pull request to the main branch with these changes, and as expected, the modified workflow was triggered and executed successfully, even though the pull request had not been reviewed, approved, or merged! Interesting. As seen in the screenshot above, the workflows triggered by my pull request were executed successfully. You might notice there are two workflow runs displayed, which I will address in the next section. For now, let's focus on the workflow labeled "test: modified GitHub workflows" at the bottom. Once the workflow was completed, I reviewed the logs, and as expected, the AWS_REGION GitHub secret was masked, as shown in the following image. This outcome was anticipated, as I had previously encountered a similar article detailing this kind of exploit, which informed my approach to this experiment. Now, if the secrets were concealed, how did the attacker manage to access them? This question led to my second key finding: 2. GitHub secrets can be exposed by making curl requests to third-party APIs within a modified workflow Yeah, you read that right! To test this, I further edited the workflow to include a request to a RequestBin I created on Pipedream. The screenshot below illustrates the updated workflow. This explains the second workflow run shown in the earlier screenshot, confirming that both workflows were executed successfully. On Pipedream's RequestBin, I was able to view the GitHub "secret" in plain text. This raised a concerning question: could anyone simply submit a pull request to an open-source project and easily access sensitive keys? Securing Your Workflows Given the potential vulnerabilities uncovered during this experiment, it’s crucial to understand how to secure GitHub workflows to prevent unauthorized access to sensitive data. GitHub provides several settings that can be configured to reduce the risk of exploitation: Actions permissions setting:
By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute.


Fork pull-request workflows from outside collaborators setting:
This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Additionally, GitHub’s documentation notes that workflows triggered from forks do not have access to sensitive data like secrets. This emphasizes the importance of reviewing the settings for repositories where sensitive data is handled. By implementing these security measures, repositories can significantly reduce the likelihood of similar vulnerabilities being exploited. Possible Explanations for the Exploit Taking all of the above factors into consideration, if the rumors are accurate and Ledger's NPM secrets were indeed compromised, a few scenarios might explain how this occurred: CASE #1: The package maintainers overlooked the configuration settings and allowed the compromised workflows to run.
CASE #2: The attacker somehow obtained full write access to the repository.
CASE #3: The attacker is, or was, a previous contributor to the project.
CASE #4: The exploit was carried out as an inside job. My Analysis Upon reviewing these scenarios, I believe that CASE #3 is the most plausible explanation. A previous contributor may not need explicit approval to trigger workflows in the repository, making it easier to exploit this vulnerability. I have seen various discussions on social media suggesting that a former employee’s account might have been compromised, which would support CASE #3. However, until an official statement is released by Ledger, the exact cause remains speculative. Final Thoughts Through this experiment, I gained a deeper understanding of how workflow vulnerabilities can be exploited and how developers can protect their repositories from such threats. By implementing the recommended security settings and thoroughly reviewing contributor permissions, open-source maintainers can minimize the risk of unauthorized access. In December 2023, it was discovered that an NPM package commonly used by decentralized web applications (dApps) had been compromised. The package in question, @ledgerhq/connect-kit , is maintained by Ledger, a well-known and arguably the most trusted provider of secure hardware wallets. Ironic right? @ledgerhq/connect-kit Well, not really, because the compromised package has nothing to do with the ledger's secure hardware wallets. However, the incident understandably raised concerns among users about the security of their assets, despite those assets being stored offline in hardware wallets. While the compromised package posed no immediate threat to Ledger's hardware devices, the situation sparked widespread discussion and speculation. The prevailing theory suggests that the compromise occurred due to a vulnerability in Ledger’s GitHub workflow. It is believed that an attacker exploited a GitHub pull request workflow to gain access to Ledger's NPM keys, enabling them to publish malicious code. The malicious update reportedly caused a secondary window to open when users attempted to connect their wallets. The Experiment The Experiment The incident piqued my curiosity, prompting me to question whether GitHub workflows were inherently flawed or if there was more nuance to the exploit. To explore this, I conducted an experiment to see if I could replicate the vulnerability. Using an existing open-source repository, I attempted to recreate the exploit. During my testing, I discovered that: 1. A pull request can edit a workflow and the new workflow will run immediately after the pull request is made 1. A pull request can edit a workflow and the new workflow will run immediately after the pull request is made The screenshot below displays the contents of a pipeline.yml file from the repository I was working with. The pipeline is configured to trigger every push to the main branch, deploying the serverless application to AWS . pipeline.yml AWS I proceeded by creating a new branch within the repository and modifying the pipeline file. The updated configuration was set to trigger the workflow on every pull request, regardless of the branch. The screenshot below illustrates the modified state of the file. Along with these modifications, I added an instruction to print the AWS_REGION GitHub secret, which was already present in the repository. I expected to see the value displayed in the workflow logs after the action was executed successfully. AWS_REGION I then submitted a pull request to the main branch with these changes, and as expected, the modified workflow was triggered and executed successfully, even though the pull request had not been reviewed, approved, or merged! Interesting. As seen in the screenshot above, the workflows triggered by my pull request were executed successfully. You might notice there are two workflow runs displayed, which I will address in the next section. For now, let's focus on the workflow labeled "test: modified GitHub workflows" at the bottom. Once the workflow was completed, I reviewed the logs, and as expected, the AWS_REGION GitHub secret was masked, as shown in the following image. This outcome was anticipated, as I had previously encountered a similar article detailing this kind of exploit, which informed my approach to this experiment. AWS_REGION Now, if the secrets were concealed, how did the attacker manage to access them? This question led to my second key finding: 2. GitHub secrets can be exposed by making curl requests to third-party APIs within a modified workflow 2. GitHub secrets can be exposed by making requests to third-party APIs within a modified workflow Yeah, you read that right! To test this, I further edited the workflow to include a request to a RequestBin I created on Pipedream . The screenshot below illustrates the updated workflow. Pipedream This explains the second workflow run shown in the earlier screenshot, confirming that both workflows were executed successfully. On Pipedream's RequestBin, I was able to view the GitHub "secret" in plain text. This raised a concerning question: could anyone simply submit a pull request to an open-source project and easily access sensitive keys? Securing Your Workflows Securing Your Workflows Given the potential vulnerabilities uncovered during this experiment, it’s crucial to understand how to secure GitHub workflows to prevent unauthorized access to sensitive data. GitHub provides several settings that can be configured to reduce the risk of exploitation: GitHub Actions permissions setting:
By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute. Fork pull-request workflows from outside collaborators setting:
This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Actions permissions setting: By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute. Actions permissions setting: Actions permissions setting: By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute. Fork pull-request workflows from outside collaborators setting: This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Fork pull-request workflows from outside collaborators setting: Fork pull-request workflows from outside collaborators setting: This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Additionally, GitHub’s documentation notes that workflows triggered from forks do not have access to sensitive data like secrets. This emphasizes the importance of reviewing the settings for repositories where sensitive data is handled. By implementing these security measures, repositories can significantly reduce the likelihood of similar vulnerabilities being exploited. Possible Explanations for the Exploit Possible Explanations for the Exploit Taking all of the above factors into consideration, if the rumors are accurate and Ledger's NPM secrets were indeed compromised, a few scenarios might explain how this occurred: CASE #1: The package maintainers overlooked the configuration settings and allowed the compromised workflows to run. CASE #2: The attacker somehow obtained full write access to the repository. CASE #3: The attacker is, or was, a previous contributor to the project. CASE #4: The exploit was carried out as an inside job. CASE #1: The package maintainers overlooked the configuration settings and allowed the compromised workflows to run. CASE #1: CASE #2: The attacker somehow obtained full write access to the repository. CASE #2: CASE #3 : The attacker is, or was, a previous contributor to the project. CASE #3 CASE #4: The exploit was carried out as an inside job. CASE #4: My Analysis My Analysis Upon reviewing these scenarios, I believe that CASE #3 is the most plausible explanation. A previous contributor may not need explicit approval to trigger workflows in the repository, making it easier to exploit this vulnerability. I have seen various discussions on social media suggesting that a former employee’s account might have been compromised, which would support CASE #3. However, until an official statement is released by Ledger, the exact cause remains speculative. Final Thoughts Final Thoughts Through this experiment, I gained a deeper understanding of how workflow vulnerabilities can be exploited and how developers can protect their repositories from such threats. By implementing the recommended security settings and thoroughly reviewing contributor permissions, open-source maintainers can minimize the risk of unauthorized access.

How a Compromised NPM Package Revealed GitHub Workflow Vulnerabilities

Table of Links Abstract and 1. Introduction Why ELIZA?
The Intelligence Engineers
Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs
From IPL to SLIP and Lisp
A Critical Tangent into Gomoku
Interpretation is the Core of Intelligence
The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion
Finally ELIZA: A Platform, Not a Chat Bot!
A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community
Another Wave: A BASIC ELIZA turns the PC Generation on to AI
Conclusion: A certain danger lurks there
Acknowledgements and References 12 Conclusion: A certain danger lurks there Weizenbaum’s goal to use ELIZA as a platform for the study of the human process of interpretation was thwarted by exactly what he did not want to see; The “kludge” [in nearly the original sense of the term] supplanted the reality. Instead of using ELIZA as a tool to study interpretation and interaction with AI, it became a cause celebre in-and-of-itself, the DOCTOR script being the only one ever seen, because it was so good for such a simple program – exactly the opposite of Weizenbaum’s point! Moreover, exactly what Weizenbaum did not want to happen with regard to Lisp vs. SLIP came to pass; instead of people using Fortran to build complex AI programs. Nearly everyone in AI, or involved in symbolic and/or list processing turned to Lisp, and SLIP eventually faded away. In 1950, Alan Turing wrote: “I believe that in about fifty years’ time it will be possible to programme computers, with a storage capacity of about 109, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent, chance of making the right identification after five minutes of questioning. The original question, ‘Can machines think!’ I believe to be too meaningless to deserve discussion. Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted. I believe further that no useful purpose is served by concealing these beliefs. The popular view that scientists proceed inexorably from well-established fact to well-established fact, never being influenced by any unproved conjecture, is quite mistaken. Provided it is made clear which are proved facts and which are conjectures, no harm can result. Conjectures are of great importance since they suggest useful lines of research.”[44, p. 442] A mere decade and a half later, Joseph Weizenbaum wrote: “With ELIZA as the basic vehicle, experiments may be set up in which the subjects find it credible to believe that the responses which appear on his[17] typewriter are generated by a human sitting at a similar instrument in another room.”[47, p. 42] Regardless of how close this description may seem to Turing’s test, Weizenbaum did not build ELIZA to pass that test. Rather he built it to run experiments, including ones akin to the Turing Test, that could be used to study human interpretive processes (especially in the case of artificial intelligence). He believed that this research was critically important, but not merely for the academic reasons that motivated Turing and most AI researchers: “[The] whole issue of the credibility (to humans) of machine output demands investigation [...] [Important] decisions increasingly tend to be made in response to computer output. The ultimately responsible human interpreter of ’What the machine says’ is, not unlike the correspondent with ELIZA, constantly faced with the need to make credibility judgments. ELIZA shows, if nothing else, how easy it is to create and maintain the illusion of understanding, hence perhaps of judgment deserving of credibility. A certain danger lurks there.”[47, pp. 42–43] The problem of how humans impute agency, correctness, and intelligence to machines is not only still present, but has become exponentially more important in recent years, with the widespread diffusion of internet bots and large language models. Our modern computational lives might have been better had Weizenbaum pursued his goal of using ELIZA to study people’s interpretive interaction with computers, and especially with AIs. Unfortunately, his fear that “[t]here is a danger [...] that the example will run away with what it is supposed to illustrate”[47, p. 43] was too prescient. Author:
(1) Jeff Shrager, Blue Dot Change and Stanford University Symbolic Systems Program (Adjunct)( jshrager@stanford.edu). This paper is available on arxiv under CC BY 4.0 license. [17] Even for the time, it is striking that Weizenbaum constantly refers to ELIZA’s interlocutors as male, given that the only example he provides of a conversation with ELIZA is (putatively) with a woman! Table of Links Abstract and 1. Introduction Abstract and 1. Introduction Why ELIZA? The Intelligence Engineers Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs From IPL to SLIP and Lisp A Critical Tangent into Gomoku Interpretation is the Core of Intelligence The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion Finally ELIZA: A Platform, Not a Chat Bot! A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community Another Wave: A BASIC ELIZA turns the PC Generation on to AI Conclusion: A certain danger lurks there Acknowledgements and References Why ELIZA? Why ELIZA? The Intelligence Engineers The Intelligence Engineers Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs From IPL to SLIP and Lisp From IPL to SLIP and Lisp A Critical Tangent into Gomoku A Critical Tangent into Gomoku Interpretation is the Core of Intelligence Interpretation is the Core of Intelligence The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion Finally ELIZA: A Platform, Not a Chat Bot! Finally ELIZA: A Platform, Not a Chat Bot! A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community Another Wave: A BASIC ELIZA turns the PC Generation on to AI Another Wave: A BASIC ELIZA turns the PC Generation on to AI Conclusion: A certain danger lurks there Conclusion: A certain danger lurks there Acknowledgements and References Acknowledgements and References 12 Conclusion: A certain danger lurks there Weizenbaum’s goal to use ELIZA as a platform for the study of the human process of interpretation was thwarted by exactly what he did not want to see; The “kludge” [in nearly the original sense of the term] supplanted the reality. Instead of using ELIZA as a tool to study interpretation and interaction with AI, it became a cause celebre in-and-of-itself, the DOCTOR script being the only one ever seen, because it was so good for such a simple program – exactly the opposite of Weizenbaum’s point! Moreover, exactly what Weizenbaum did not want to happen with regard to Lisp vs. SLIP came to pass; instead of people using Fortran to build complex AI programs. Nearly everyone in AI, or involved in symbolic and/or list processing turned to Lisp, and SLIP eventually faded away. In 1950, Alan Turing wrote: “I believe that in about fifty years’ time it will be possible to programme computers, with a storage capacity of about 109, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent, chance of making the right identification after five minutes of questioning. The original question, ‘Can machines think!’ I believe to be too meaningless to deserve discussion. Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted. I believe further that no useful purpose is served by concealing these beliefs. The popular view that scientists proceed inexorably from well-established fact to well-established fact, never being influenced by any unproved conjecture, is quite mistaken. Provided it is made clear which are proved facts and which are conjectures, no harm can result. Conjectures are of great importance since they suggest useful lines of research.”[44, p. 442] A mere decade and a half later, Joseph Weizenbaum wrote: “With ELIZA as the basic vehicle, experiments may be set up in which the subjects find it credible to believe that the responses which appear on his[17] typewriter are generated by a human sitting at a similar instrument in another room.”[47, p. 42] Regardless of how close this description may seem to Turing’s test, Weizenbaum did not build ELIZA to pass that test. Rather he built it to run experiments, including ones akin to the Turing Test, that could be used to study human interpretive processes (especially in the case of artificial intelligence). He believed that this research was critically important, but not merely for the academic reasons that motivated Turing and most AI researchers: “[The] whole issue of the credibility (to humans) of machine output demands investigation [...] [Important] decisions increasingly tend to be made in response to computer output. The ultimately responsible human interpreter of ’What the machine says’ is, not unlike the correspondent with ELIZA, constantly faced with the need to make credibility judgments. ELIZA shows, if nothing else, how easy it is to create and maintain the illusion of understanding, hence perhaps of judgment deserving of credibility. A certain danger lurks there.”[47, pp. 42–43] The problem of how humans impute agency, correctness, and intelligence to machines is not only still present, but has become exponentially more important in recent years, with the widespread diffusion of internet bots and large language models. Our modern computational lives might have been better had Weizenbaum pursued his goal of using ELIZA to study people’s interpretive interaction with computers, and especially with AIs. Unfortunately, his fear that “[t]here is a danger [...] that the example will run away with what it is supposed to illustrate”[47, p. 43] was too prescient. Author: (1) Jeff Shrager, Blue Dot Change and Stanford University Symbolic Systems Program (Adjunct)( jshrager@stanford.edu). Author: Author: (1) Jeff Shrager, Blue Dot Change and Stanford University Symbolic Systems Program (Adjunct)( jshrager@stanford.edu). This paper is available on arxiv under CC BY 4.0 license. This paper is available on arxiv under CC BY 4.0 license. available on arxiv available on arxiv [17] Even for the time, it is striking that Weizenbaum constantly refers to ELIZA’s interlocutors as male, given that the only example he provides of a conversation with ELIZA is (putatively) with a woman!

How ELIZA’s Success Revealed the Pitfalls of Machine Credibility

In Hong Kong, where towering skyscrapers kiss the clouds and neon lights paint the night sky, a different kind of revolution is brewing - it's a revolution of pixels and code, of digital art and decentralized finance. But halfway across the world, in the bustling streets of Johannesburg or the sun-baked plazas of San Salvador, the same technology is sparking a transformation of an entirely different flavor. This tale of two crypto worlds was the subject of a riveting keynote address by Ben Caselin, Chief Marketing Officer of VALR, at the recent Foresight 2024 Hong Kong conference. I couldn't help but feel like I was witnessing the unveiling of a secret map – one that charted the diverse and often surprising ways cryptocurrency is reshaping our global financial landscape. A Digital Tale of Two Cities "Imagine, if you will, two parallel universes of crypto adoption," Caselin began, his voice carrying a hint of excitement. "In one, we have the glitzy world of Hong Kong, where crypto is the new haute couture of finance. In the other, we have the vibrant emerging markets of Africa and Latin America, where crypto is more akin to a financial Swiss Army knife." This stark contrast formed the backbone of Caselin's presentation, as he deftly navigated the three dimensions of crypto transformation: cultural, financial, and monetary. Where Crypto Meets Culture In Hong Kong, Caselin explained, the crypto revolution is as much about art and community as it is about finance. "Walk down the streets of Central, and you're as likely to overhear conversations about the latest NFT drop as you are about stock prices," he quipped. Indeed, Hong Kong has embraced the cultural aspects of crypto with open arms. From NFT galleries popping up in Sheung Wan to Web3 meetups in Lan Kwai Fong, the city has become a playground for digital innovation. Even traditional financial institutions are getting in on the act, with the recent launch of Bitcoin and Ethereum ETFs signaling a new era of crypto-finance fusion. Crypto as a Financial Lifeline But as we turn our gaze to countries like El Salvador, South Africa, and beyond, a different picture emerges. Here, cryptocurrency isn't just a novelty or an investment vehicle – it's a vital tool for financial empowerment. "In these regions, we're witnessing a rapid shift towards financial participation through crypto," Caselin emphasized. "It's not about buying digital art or speculating on the next big token. It's about sending money home to your family without exorbitant fees, or protecting your savings from runaway inflation." This financial transformation is perhaps most evident in the realm of remittances. According to World Bank data, remittances to low- and middle-income countries reached a staggering $589 billion in 2021. Crypto-powered solutions are increasingly capturing a slice of this pie, offering faster and cheaper alternatives to traditional money transfer services. Emerging Markets, Where Bitcoin is Lifeline But perhaps the most intriguing – and potentially disruptive – aspect of crypto adoption in emerging markets is the possibility of monetary transformation. Caselin hinted at a future where some countries might begin to decouple from established fiat currencies, using cryptocurrencies as a means to assert financial sovereignty. "It's not just about Bitcoin becoming legal tender in El Salvador," he explained. "It's about the potential for entire economies to reimagine their relationship with money." VALR: Bridging the Crypto Divide As the presentation drew to a close, Caselin turned his attention to VALR's role in this global crypto narrative. With over 1,000 corporate and institutional clients and nearly 700,000 individual traders, the Johannesburg-based exchange is positioning itself as a bridge between the two worlds of crypto adoption. "Our mission is to provide the robust infrastructure needed to support local fintechs and accelerate the adoption of digital assets," Caselin stated. "Whether it's a hedge fund in Hong Kong or a mobile money provider in Nairobi, we're here to facilitate their participation in the crypto economy." The crypto revolution, it seems, is not a one-size-fits-all phenomenon. Instead, it's a chameleon-like force, adapting to the unique needs and challenges of different markets. And in this ever-evolving landscape, companies like VALR are not just observers – they're active participants, helping to shape the future of finance one transaction at a time. The tale of two crypto worlds continues to unfold. And if Caselin's insights are anything to go by, the next chapter promises to be even more exciting than the last. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR In Hong Kong, where towering skyscrapers kiss the clouds and neon lights paint the night sky, a different kind of revolution is brewing - it's a revolution of pixels and code, of digital art and decentralized finance. But halfway across the world, in the bustling streets of Johannesburg or the sun-baked plazas of San Salvador, the same technology is sparking a transformation of an entirely different flavor. This tale of two crypto worlds was the subject of a riveting keynote address by Ben Caselin, Chief Marketing Officer of VALR , at the recent Foresight 2024 Hong Kong conference. I couldn't help but feel like I was witnessing the unveiling of a secret map – one that charted the diverse and often surprising ways cryptocurrency is reshaping our global financial landscape. VALR A Digital Tale of Two Cities "Imagine, if you will, two parallel universes of crypto adoption," Caselin began, his voice carrying a hint of excitement. "In one, we have the glitzy world of Hong Kong, where crypto is the new haute couture of finance. In the other, we have the vibrant emerging markets of Africa and Latin America, where crypto is more akin to a financial Swiss Army knife." This stark contrast formed the backbone of Caselin's presentation, as he deftly navigated the three dimensions of crypto transformation: cultural, financial, and monetary. Where Crypto Meets Culture In Hong Kong, Caselin explained, the crypto revolution is as much about art and community as it is about finance. "Walk down the streets of Central, and you're as likely to overhear conversations about the latest NFT drop as you are about stock prices," he quipped. Indeed, Hong Kong has embraced the cultural aspects of crypto with open arms. From NFT galleries popping up in Sheung Wan to Web3 meetups in Lan Kwai Fong, the city has become a playground for digital innovation. Even traditional financial institutions are getting in on the act, with the recent launch of Bitcoin and Ethereum ETFs signaling a new era of crypto-finance fusion. Crypto as a Financial Lifeline But as we turn our gaze to countries like El Salvador, South Africa, and beyond, a different picture emerges. Here, cryptocurrency isn't just a novelty or an investment vehicle – it's a vital tool for financial empowerment. "In these regions, we're witnessing a rapid shift towards financial participation through crypto," Caselin emphasized. "It's not about buying digital art or speculating on the next big token. It's about sending money home to your family without exorbitant fees, or protecting your savings from runaway inflation." "It's not about buying digital art or speculating on the next big token. It's about sending money home to your family without exorbitant fees, or protecting your savings from runaway inflation." This financial transformation is perhaps most evident in the realm of remittances. According to World Bank data , remittances to low- and middle-income countries reached a staggering $589 billion in 2021. Crypto-powered solutions are increasingly capturing a slice of this pie, offering faster and cheaper alternatives to traditional money transfer services. According to World Bank data Emerging Markets, Where Bitcoin is Lifeline But perhaps the most intriguing – and potentially disruptive – aspect of crypto adoption in emerging markets is the possibility of monetary transformation. Caselin hinted at a future where some countries might begin to decouple from established fiat currencies, using cryptocurrencies as a means to assert financial sovereignty. "It's not just about Bitcoin becoming legal tender in El Salvador," he explained. "It's about the potential for entire economies to reimagine their relationship with money." "It's about the potential for entire economies to reimagine their relationship with money." VALR: Bridging the Crypto Divide As the presentation drew to a close, Caselin turned his attention to VALR's role in this global crypto narrative. With over 1,000 corporate and institutional clients and nearly 700,000 individual traders, the Johannesburg-based exchange is positioning itself as a bridge between the two worlds of crypto adoption. "Our mission is to provide the robust infrastructure needed to support local fintechs and accelerate the adoption of digital assets," Caselin stated. "Whether it's a hedge fund in Hong Kong or a mobile money provider in Nairobi, we're here to facilitate their participation in the crypto economy." "Whether it's a hedge fund in Hong Kong or a mobile money provider in Nairobi, we're here to facilitate their participation in the crypto economy." The crypto revolution, it seems, is not a one-size-fits-all phenomenon. Instead, it's a chameleon-like force, adapting to the unique needs and challenges of different markets. And in this ever-evolving landscape, companies like VALR are not just observers – they're active participants, helping to shape the future of finance one transaction at a time. The tale of two crypto worlds continues to unfold. And if Caselin's insights are anything to go by, the next chapter promises to be even more exciting than the last. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

VALR CMO Ben Caselin Reveals How Digital Assets are Reshaping Finance in Unexpected Ways

VALR সিএমও বেন ক্যাসেলিন প্রকাশ করেছেন কীভাবে ডিজিটাল সম্পদ অপ্রত্যাশিত উপায়ে অর্থকে পুনর্নির্মাণ করছে

VALR CMO Ben Caselin enthüllt, wie digitale Assets die Finanzwelt auf unerwartete Weise umgestalten

Ben Caselin, director de marketing de VALR, revela cómo los activos digitales están transformando las finanzas de maneras inesperadas

Ben Caselin, directeur marketing de VALR, révèle comment les actifs numériques transforment la finance de manière inattendue

वीएएलआर के सीएमओ बेन केसेलिन ने बताया कि कैसे डिजिटल परिसंपत्तियां अप्रत्याशित तरीकों से वित्त को नया रूप दे रही हैं

VALR CMO ベン・ケースリンが、デジタル資産が金融を予想外の形で変革させていることを明かす

VALR CMO Ben Caselin이 디지털 자산이 예상치 못한 방식으로 금융을 어떻게 재편하고 있는지 공개

O CMO da VALR, Ben Caselin, revela como os ativos digitais estão remodelando as finanças de maneiras inesperadas

Директор по маркетингу VALR Бен Каселин рассказывает, как цифровые активы неожиданным образом меняют финансы

VALR CMO'su Ben Caselin, dijital varlıkların finansı beklenmedik şekillerde nasıl yeniden şekillendirdiğini açıklıyor

Giám đốc tiếp thị của VALR Ben Caselin tiết lộ cách tài sản kỹ thuật số đang định hình lại tài chính theo những cách không ngờ tới

VALR 首席营销官 Ben Caselin 揭示数字资产如何以意想不到的方式重塑金融

Court Reveals Wright's 2024 MYOB Email Was Manipulated to Support False Claims

COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 30 of 42. 28. Economics of BitCoin Nodes (Reliance Document) {ID_000227} / {L3/219/1} 523. The document purports to contain notes relating to “The Economics of central core BitCoin Nodes” and is dated as if it was created in the period September-October 2008. (a) COPA’s Reasons for Alleging Forgery 524. The document has been backdated. Within the document are several hidden embedded zip files containing references to Microsoft Schema dating from 2014-2015 which did not exist in 2008. These references are not visible to someone editing the document or reviewing its internal content without forensic analysis. [PM26 [16-17]]. 525. Equations within {ID_000227} were created with MathType software v6.9, a version dating from February 2013 which did not exist in 2008. [PM40 [32, 42]]. 526. The document contains redundant hidden content of previous edits which do not appear on the face of the document. [PM26 [19-20]]. 527. The hidden embedded text within the document includes references to a web page URL which did not exist until on or after 11 April 2019. [PM26 [21]]. 528. The reference to the 11 April 2019 URL has been deleted from the face of the document and replaced with a footnote which appears to be a “note to self” about what would need to be added in a future draft (“Note: I will need to link to laws such as the CFAA (USA) – see LLM[…]”). Other footnotes have been introduced or edited to refer to Bitcoin in the future tense. The misleading effect of these edits is to make the document appear as if it was created at a time before Bitcoin was created. In fact, the document was created later, after 11 April 2019, and the anachronistic content was obscured by editing. [PM26 [19-24]]. 529. The document was created from a precursor document after 11 April 2019. No precursor document has been disclosed by Dr Wright. [PM26 [23]]. 530. The document {ID_000227} has an implausible edit time of 20 days 19 hours and 22 minutes consistent with the use of clock manipulation techniques. [PM26 [6-10]]. 531. The document was emailed from Dr Wright to Lynn Wright on 18 January 2020. The email contains several manipulated documents purported to be in the custody of Lynn Wright. The metadata of that zip file is also irregular. [{ID_003937}, PM26 [1, 25-38]]. (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility 532. The effect of the tampering is to make the document appear to be supportive of Dr Wright’s claim to be Satoshi Nakamoto (suggesting work done by him in September / October 2008 which looked ahead to Bitcoin), contrary to fact. 533. Although the document metadata purports Lynn Wright to have been an author, it was actually created by Dr Wright in the name of Lynn Wright after 11 April 2019, and a copy later sent from Dr Wright to Lynn Wright by email long after they were separated, contained in a zip file along with many other files bearing evidence of backdating and tampering including several documents on which Dr Wright primarily relies. The metadata of that zip file is itself also irregular. [{ID_003927}, PM26 [1, 25-38]]. 534. Dr Wright shared a document with identical content on social media on 16 January 2020, contemporaneously with the aforesaid email to Lynn Wright. Upon request in these proceedings, Dr Wright has repeatedly declined to disclose a copy of his posts to social media accounts. Since the date of the Request, Dr Wright has claimed to have lost access to the relevant social media account. 535. The content introduced into the document, having the effect of making it appear to date from earlier than its true date, is phrased in the first person as a note from Dr Wright to himself. 536. In his first witness statement in these proceedings, Dr Wright lists this document as a document to which he has been referred when preparing his evidence. 537. Dr Wright is recorded in the metadata as the first author. 538. Dr Wright has not disclosed the precursor documents [PM26 [23]]. (c) Dr Wright’s Explanations and COPA’s Rebuttal 539. Dr Wright sought to explain away the presence of anachronistic references to Mathtype software and Microsoft schemas by referring to the effects of his computing environment in supposedly causing such elements to be inserted into documents merely through a document being opened (without any user interaction): Wright11 Appendix B, [6.3 to 6.4]{CSW/2/20}. 540. Dr Wright sought to explain the presence of remnant text, including the URL in the footnote dating from 2019, by saying that text from another document had become merged with the text of this document as a result of features of his computing environment: Wright11 Appendix B, [6.5 to 6.6] {CSW/2/20}. He also suggested that the article at the URL had limited relevance to the material content of his document. 541. COPA submitted that this explanation should be rejected as dishonest for the following reasons: 541.1. Dr Wright’s explanation is contradicted by the clear expert evidence of Mr Madden, which is that the Mathtype references and schema references could not be inserted without the document being interacted with by a user, which would in turn result in updating of the metadata timestamps of the document. The fact that the metadata timestamps for this document were dated to 2008 but the raw data contained the elements set out above shows that the document has been forged by backdating. See Madden4, [158]; Madden / Placks joint statement2 at [8]; {Day16/35:19} to {Day16/38:11}; {Day16/125:7} to {Day16/125:18}. 541.2. It is wildly implausible that the features of a shared computing environment would cause two documents to become merged, and to do so in a way which resulted in the document not being corrupted and appearing normal on its face. See Madden4, [159]; Madden / Placks joint statement2 at [8]. 541.3. In his evidence, Dr Wright tried to justify his position by going so far as to claim implausibly that any digital document more than a few years’ old could be expected to have anomalous features in its raw data. He claimed never to have seen a file older than five years which was pristine in metadata, before being compelled to accept that the Bitcoin White Paper is pristine {Day3/20:5} to {Day3/20:25}. 541.4. In his evidence, Dr Wright attempted to explain that the footnote in the edited version of the document was obviously more apt to the text than the footnote in the remnant text. In doing so, he put forward a bizarre interpretation of the Bitcoin system in which the availability of injunctive relief is supposedly essential to preventing subversion of the system: {Day3/7:18} to {Day3/15:16}. (d) Conclusion 542. The points on this document gathered in Appendix 1 to Dr Wright’s Closing repeat a number of points I have already found to be unconvincing in relation to {ID_000217} above and they are equally unconvincing here. Furthermore, the argument that this document is the result of text from another document becoming merged into the document is particularly absurd. The argument presupposes disk read errors such that a disk sector containing a portion of another document is merged into the saved version of this document but without any trace of corruption or discontinuity. 543. In short, I found Dr Wright’s explanations wholly unconvincing, especially in the light of the detailed specific points made by Mr Madden. This document was plainly forged, and forged by Dr Wright. 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 January 29, 2024, judiciary.uk 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. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 30 of 42. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part of this filing here . This part is 30 of 42. HackerNoon’s Legal PDF Series HackerNoon’s Legal PDF Series here here 28. Economics of BitCoin Nodes (Reliance Document) {ID_000227} / {L3/219/1} 523. The document purports to contain notes relating to “The Economics of central core BitCoin Nodes” and is dated as if it was created in the period September-October 2008. (a) COPA’s Reasons for Alleging Forgery (a) COPA’s Reasons for Alleging Forgery 524. The document has been backdated. Within the document are several hidden embedded zip files containing references to Microsoft Schema dating from 2014-2015 which did not exist in 2008. These references are not visible to someone editing the document or reviewing its internal content without forensic analysis. [PM26 [16-17]]. 525. Equations within {ID_000227} were created with MathType software v6.9, a version dating from February 2013 which did not exist in 2008. [PM40 [32, 42]]. 526. The document contains redundant hidden content of previous edits which do not appear on the face of the document. [PM26 [19-20]]. 527. The hidden embedded text within the document includes references to a web page URL which did not exist until on or after 11 April 2019. [PM26 [21]]. 528. The reference to the 11 April 2019 URL has been deleted from the face of the document and replaced with a footnote which appears to be a “note to self” about what would need to be added in a future draft (“Note: I will need to link to laws such as the CFAA (USA) – see LLM[…]”). Other footnotes have been introduced or edited to refer to Bitcoin in the future tense. The misleading effect of these edits is to make the document appear as if it was created at a time before Bitcoin was created. In fact, the document was created later, after 11 April 2019, and the anachronistic content was obscured by editing. [PM26 [19-24]]. 529. The document was created from a precursor document after 11 April 2019. No precursor document has been disclosed by Dr Wright. [PM26 [23]]. 530. The document {ID_000227} has an implausible edit time of 20 days 19 hours and 22 minutes consistent with the use of clock manipulation techniques. [PM26 [6-10]]. 531. The document was emailed from Dr Wright to Lynn Wright on 18 January 2020. The email contains several manipulated documents purported to be in the custody of Lynn Wright. The metadata of that zip file is also irregular. [{ID_003937}, PM26 [1, 25-38]]. (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility 532. The effect of the tampering is to make the document appear to be supportive of Dr Wright’s claim to be Satoshi Nakamoto (suggesting work done by him in September / October 2008 which looked ahead to Bitcoin), contrary to fact. 533. Although the document metadata purports Lynn Wright to have been an author, it was actually created by Dr Wright in the name of Lynn Wright after 11 April 2019, and a copy later sent from Dr Wright to Lynn Wright by email long after they were separated, contained in a zip file along with many other files bearing evidence of backdating and tampering including several documents on which Dr Wright primarily relies. The metadata of that zip file is itself also irregular. [{ID_003927}, PM26 [1, 25-38]]. 534. Dr Wright shared a document with identical content on social media on 16 January 2020, contemporaneously with the aforesaid email to Lynn Wright. Upon request in these proceedings, Dr Wright has repeatedly declined to disclose a copy of his posts to social media accounts. Since the date of the Request, Dr Wright has claimed to have lost access to the relevant social media account. 535. The content introduced into the document, having the effect of making it appear to date from earlier than its true date, is phrased in the first person as a note from Dr Wright to himself. 536. In his first witness statement in these proceedings, Dr Wright lists this document as a document to which he has been referred when preparing his evidence. 537. Dr Wright is recorded in the metadata as the first author. 538. Dr Wright has not disclosed the precursor documents [PM26 [23]]. (c) Dr Wright’s Explanations and COPA’s Rebuttal (c) Dr Wright’s Explanations and COPA’s Rebuttal 539. Dr Wright sought to explain away the presence of anachronistic references to Mathtype software and Microsoft schemas by referring to the effects of his computing environment in supposedly causing such elements to be inserted into documents merely through a document being opened (without any user interaction): Wright11 Appendix B, [6.3 to 6.4]{CSW/2/20}. 540. Dr Wright sought to explain the presence of remnant text, including the URL in the footnote dating from 2019, by saying that text from another document had become merged with the text of this document as a result of features of his computing environment: Wright11 Appendix B, [6.5 to 6.6] {CSW/2/20}. He also suggested that the article at the URL had limited relevance to the material content of his document. 541. COPA submitted that this explanation should be rejected as dishonest for the following reasons: 541.1. Dr Wright’s explanation is contradicted by the clear expert evidence of Mr Madden, which is that the Mathtype references and schema references could not be inserted without the document being interacted with by a user, which would in turn result in updating of the metadata timestamps of the document. The fact that the metadata timestamps for this document were dated to 2008 but the raw data contained the elements set out above shows that the document has been forged by backdating. See Madden4, [158]; Madden / Placks joint statement2 at [8]; {Day16/35:19} to {Day16/38:11}; {Day16/125:7} to {Day16/125:18}. 541.2. It is wildly implausible that the features of a shared computing environment would cause two documents to become merged, and to do so in a way which resulted in the document not being corrupted and appearing normal on its face. See Madden4, [159]; Madden / Placks joint statement2 at [8]. 541.3. In his evidence, Dr Wright tried to justify his position by going so far as to claim implausibly that any digital document more than a few years’ old could be expected to have anomalous features in its raw data. He claimed never to have seen a file older than five years which was pristine in metadata, before being compelled to accept that the Bitcoin White Paper is pristine {Day3/20:5} to {Day3/20:25}. 541.4. In his evidence, Dr Wright attempted to explain that the footnote in the edited version of the document was obviously more apt to the text than the footnote in the remnant text. In doing so, he put forward a bizarre interpretation of the Bitcoin system in which the availability of injunctive relief is supposedly essential to preventing subversion of the system: {Day3/7:18} to {Day3/15:16}. (d) Conclusion (d) Conclusion 542. The points on this document gathered in Appendix 1 to Dr Wright’s Closing repeat a number of points I have already found to be unconvincing in relation to {ID_000217} above and they are equally unconvincing here. Furthermore, the argument that this document is the result of text from another document becoming merged into the document is particularly absurd. The argument presupposes disk read errors such that a disk sector containing a portion of another document is merged into the saved version of this document but without any trace of corruption or discontinuity. 543. In short, I found Dr Wright’s explanations wholly unconvincing, especially in the light of the detailed specific points made by Mr Madden. This document was plainly forged, and forged by Dr Wright. 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 January 29, 2024, judiciary.uk 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 January 29, 2024, judiciary.uk 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. judiciary.uk judiciary.uk

Forensic Analysis Reveals Backdating in Craig Wright’s Bitcoin Node Economics Paper

Court Reveals Craig Wright's Bitcoin White Paper LaTeX Files as Recent Forgeries

Stories, News & Mentions about REVEA

Revea’s Stories on HackerNoon