Moonfare

moonfare

Mispricing Opportunities: Underserved Small Business Segments Immigrant communities are the heartbeat of American entrepreneurship. They’re launching startups, scaling innovations, creating jobs, and driving economic growth. According to payroll company Gusto, immigrants have formed about around 20% of new businesses, with rates over 40% in some states. A more recent study at MIT reveals, on a per capita basis, newcomers are 80% more likely to start their own businesses than US-born citizens. In fact, many of the biggest names in tech—Google, SpaceX, and Zoom—were founded by immigrants, highlighting the fact that nearly 55% of America’s billion-dollar startups have immigrant origins. But despite their entrepreneurial drive and solid track records, immigrant business owners face steep barriers to accessing affordable funding sources. The data is clear: immigrant and minority entrepreneurs are denied bank loans more frequently than average applicants regardless of their credit scores - even if they are found to have lower delinquencies. These founders face higher scrutiny around income verification and asset documentation, creating a nearly impenetrable barrier to capital. This underserved market is significant. About 5 million new businesses (mainly small or micro) are formed every year, with around 20% owned by immigrants. Assuming half of these immigrant-backed businesses survive their first 5 years and roughly 40% of them seek a loan, this translates into approximately 300 thousand potential new credit customers in the market annually. Of these, 70% could get approved for a loan averaging nearly $500 thousand each*. For lenders, they might have looked into but essentially ignored a more than $70B lending market by origination volume. Moreover, such credit relationships might unlock cross-selling opportunities, creating extra revenue streams to lenders. Drivers of Mispricing The challenges for immigrant founders are often systemic. Language barriers, cultural obstacles, and rigid documentation standards make for a complex landscape. Without conventional documentation, US credit histories, or W2 incomes, many simply don’t fit the mold set by traditional underwriting standards. This gap leaves many entrepreneurs relying on costly equity financing or informal funding from personal or family sources. Yet hope on the horizon. The fintech sector is stepping in, offering innovative, tech-driven solutions designed to serve this overlooked market segment. Technologies Unlocking Origination and Underwriting With advancements in artificial intelligence (AI) and Open Banking regulatory reforms (like 1033 rulemaking), we’re seeing real change in how lenders assess creditworthiness. Cash flow-based underwriting model looks beyond credit scores, focusing instead on business dynamics like bank transactions, customer relationships, and revenue streams. Take this scenario: a small business supplies materials to a reputable, large-scale manufacturer. That stable client relationship could be the key factor in determining lending eligibility. APIs and alternative data sources generated through AI/machine learning technologies could additionally include 20-500 data points, making risk assessment more comprehensive. On individual entrepreneurs specifically, their alternative personal scoring could be as accurate as traditional methodology. Combined with conventional scores, total assessment results could offer a nearly 5% lift on model predictive performance for risk differentiation. Innovative Funding and Distribution Channels As origination and underwriting evolve, so do the sources and methods of distributing originated small business loans along the credit value chain. Here’s a breakdown: Diverse Funding Sources: The cautious stance of traditional banks has paved the way for private funders to step up. Percent and YieldStreet have been democratizing access to small business lending, allowing a broader range of individual accredited investors to get involved. Additionally, companies like Bluevine leverage larger-scale asset managers/private credit funds to support small businesses at scale.


Digitized Distribution Platforms: Platforms like iCapital, CAIS, and Moonfare are making institutional private credit more accessible and streamlined. These platforms enable wealth advisors (e.g., RIAs and independent broker-dealers) to connect private credit funds with accredited investors and family offices, minimizing operational burdens. For investors, this approach offers exposure to lending opportunities that are diversified and professionally managed, similar to a mutual fund experience.


Secondary Market Innovations: Secondary markets for small business revenue-based financial assets are creating an exciting new space. An increasing number of secondary marketplaces have emerged and allowed investors to trade small business loan shares like stocks. By leveraging innovations like blockchain, these markets could unlock new funding channels for entrepreneurs, even as they remain niche for now. Micro Connect Financial Assets Exchange (MCEX), for example, is a licensed revenue-based financing exchange out of China. It enables small businesses to raise capital through revenue-based financing that can be traded like stock shares or ETFs. MCEX has set an inspiring example for US lenders and investors, showing a transparent, flexible, and scalable pathway for funding for small business owners in America, combining liquidity with steady cash distributions. Immigrant and minority-owned businesses are indispensable to the American economic growth. But traditional funding hasn’t kept pace, leaving many small business loans mispriced. As technology reshapes lending and distribution, the small business financing market is set for a transformative evolution, bringing inclusivity, cost savings, and increased liquidity to the forefront. Notes: Triangulated using average SBA (7) loan size as well as interview data by the author
Information only. No investment advice provided in this article
Revenue-based financing can be packaged into loans and other credit instruments; only focused on loans in this article Feature Image*: Google co-founder Sergey Brin (left) came to the US at the age of 6* Mispricing Opportunities: Underserved Small Business Segments Mispricing Opportunities: Underserved Small Business Segments Immigrant communities are the heartbeat of American entrepreneurship. They’re launching startups, scaling innovations, creating jobs, and driving economic growth. According to payroll company Gusto , immigrants have formed about around 20% of new businesses, with rates over 40% in some states. A more recent study at MIT reveals, on a per capita basis, newcomers are 80% more likely to start their own businesses than US-born citizens. In fact, many of the biggest names in tech—Google, SpaceX, and Zoom—were founded by immigrants, highlighting the fact that nearly 55% of America’s billion-dollar startups have immigrant origins . payroll company Gusto 20% 40% A more recent study at MIT 80% 55% 55% of America’s billion-dollar startups have immigrant origins But despite their entrepreneurial drive and solid track records, immigrant business owners face steep barriers to accessing affordable funding sources. The data is clear: immigrant and minority entrepreneurs are denied bank loans more frequently than average applicants regardless of their credit scores - even if they are found to have lower delinquencies. These founders face higher scrutiny around income verification and asset documentation, creating a nearly impenetrable barrier to capital. denied bank loans more frequently regardless of their credit scores - even if they are found to have lower delinquencies. This underserved market is significant. About 5 million new businesses (mainly small or micro) are formed every year, with around 20% owned by immigrants. Assuming half of these immigrant-backed businesses survive their first 5 years and roughly 40% of them seek a loan, this translates into approximately 300 thousand potential new credit customers in the market annually. Of these, 70% could get approved for a loan averaging nearly $500 thousand each*. For lenders, they might have looked into but essentially ignored a more than $70B lending market by origination volume. Moreover, such credit relationships might unlock cross-selling opportunities, creating extra revenue streams to lenders. This underserved market is significant. 20% first 5 years 40% 300 70% $500 thousand For lenders, they might have looked into but essentially ignored a more than $70B lending market by origination volume. For lenders, they might have looked into but essentially ignored a more than $70B lending market by origination volume. Drivers of Mispricing Drivers of Mispricing The challenges for immigrant founders are often systemic. Language barriers, cultural obstacles, and rigid documentation standards make for a complex landscape. Without conventional documentation, US credit histories, or W2 incomes, many simply don’t fit the mold set by traditional underwriting standards. This gap leaves many entrepreneurs relying on costly equity financing or informal funding from personal or family sources. Yet hope on the horizon. The fintech sector is stepping in, offering innovative, tech-driven solutions designed to serve this overlooked market segment. Technologies Unlocking Origination and Underwriting Technologies Unlocking Origination and Underwriting With advancements in artificial intelligence (AI) and Open Banking regulatory reforms (like 1033 rulemaking ), we’re seeing real change in how lenders assess creditworthiness. Cash flow-based underwriting model looks beyond credit scores, focusing instead on business dynamics like bank transactions, customer relationships, and revenue streams. Take this scenario: a small business supplies materials to a reputable, large-scale manufacturer. That stable client relationship could be the key factor in determining lending eligibility. 1033 rulemaking 1033 rulemaking APIs and alternative data sources generated through AI/machine learning technologies could additionally include 20-500 data points, making risk assessment more comprehensive. On individual entrepreneurs specifically, their alternative personal scoring could be as accurate as traditional methodology. Combined with conventional scores, total assessment results could offer a nearly 5% lift on model predictive performance for risk differentiation. 20-500 5% Innovative Funding and Distribution Channels Innovative Funding and Distribution Channels As origination and underwriting evolve, so do the sources and methods of distributing originated small business loans along the credit value chain. Here’s a breakdown: Diverse Funding Sources: The cautious stance of traditional banks has paved the way for private funders to step up. Percent and YieldStreet have been democratizing access to small business lending, allowing a broader range of individual accredited investors to get involved. Additionally, companies like Bluevine leverage larger-scale asset managers/private credit funds to support small businesses at scale. Digitized Distribution Platforms: Platforms like iCapital, CAIS, and Moonfare are making institutional private credit more accessible and streamlined. These platforms enable wealth advisors (e.g., RIAs and independent broker-dealers) to connect private credit funds with accredited investors and family offices, minimizing operational burdens. For investors, this approach offers exposure to lending opportunities that are diversified and professionally managed, similar to a mutual fund experience. Secondary Market Innovations: Secondary markets for small business revenue-based financial assets are creating an exciting new space. An increasing number of secondary marketplaces have emerged and allowed investors to trade small business loan shares like stocks. By leveraging innovations like blockchain, these markets could unlock new funding channels for entrepreneurs, even as they remain niche for now. Micro Connect Financial Assets Exchange (MCEX), for example, is a licensed revenue-based financing exchange out of China. It enables small businesses to raise capital through revenue-based financing that can be traded like stock shares or ETFs. MCEX has set an inspiring example for US lenders and investors, showing a transparent, flexible, and scalable pathway for funding for small business owners in America, combining liquidity with steady cash distributions. Diverse Funding Sources: The cautious stance of traditional banks has paved the way for private funders to step up. Percent and YieldStreet have been democratizing access to small business lending, allowing a broader range of individual accredited investors to get involved. Additionally, companies like Bluevine leverage larger-scale asset managers/private credit funds to support small businesses at scale. Diverse Funding Sources : The cautious stance of traditional banks has paved the way for private funders to step up. Percent and YieldStreet have been democratizing access to small business lending, allowing a broader range of individual accredited investors to get involved. Additionally, companies like Bluevine leverage larger-scale asset managers/private credit funds to support small businesses at scale. Diverse Funding Sources larger-scale asset managers/private credit funds Digitized Distribution Platforms: Platforms like iCapital, CAIS, and Moonfare are making institutional private credit more accessible and streamlined. These platforms enable wealth advisors (e.g., RIAs and independent broker-dealers) to connect private credit funds with accredited investors and family offices, minimizing operational burdens. For investors, this approach offers exposure to lending opportunities that are diversified and professionally managed, similar to a mutual fund experience. Digitized Distribution Platforms : Platforms like iCapital, CAIS, and Moonfare are making institutional private credit more accessible and streamlined. These platforms enable wealth advisors ( e.g., RIAs and independent broker-dealers ) to connect private credit funds with accredited investors and family offices, minimizing operational burdens. For investors, this approach offers exposure to lending opportunities that are diversified and professionally managed, similar to a mutual fund experience. Digitized Distribution Platforms e.g., RIAs and independent broker-dealers Secondary Market Innovations: Secondary markets for small business revenue-based financial assets are creating an exciting new space. An increasing number of secondary marketplaces have emerged and allowed investors to trade small business loan shares like stocks. By leveraging innovations like blockchain, these markets could unlock new funding channels for entrepreneurs, even as they remain niche for now. Micro Connect Financial Assets Exchange (MCEX), for example, is a licensed revenue-based financing exchange out of China. It enables small businesses to raise capital through revenue-based financing that can be traded like stock shares or ETFs. MCEX has set an inspiring example for US lenders and investors, showing a transparent, flexible, and scalable pathway for funding for small business owners in America, combining liquidity with steady cash distributions. Secondary Market Innovations : Secondary markets for small business revenue-based financial assets are creating an exciting new space. An increasing number of secondary marketplaces have emerged and allowed investors to trade small business loan shares like stocks. By leveraging innovations like blockchain, these markets could unlock new funding channels for entrepreneurs, even as they remain niche for now. Micro Connect Financial Assets Exchange (MCEX) , for example, is a licensed revenue-based financing exchange out of China. It enables small businesses to raise capital through revenue-based financing that can be traded like stock shares or ETFs. MCEX has set an inspiring example for US lenders and investors, showing a transparent, flexible, and scalable pathway for funding for small business owners in America, combining liquidity with steady cash distributions. Secondary Market Innovations Micro Connect Financial Assets Exchange (MCEX) Immigrant and minority-owned businesses are indispensable to the American economic growth. But traditional funding hasn’t kept pace, leaving many small business loans mispriced. As technology reshapes lending and distribution, the small business financing market is set for a transformative evolution, bringing inclusivity, cost savings, and increased liquidity to the forefront. Notes: Notes: Notes: Triangulated using average SBA (7) loan size as well as interview data by the author Information only. No investment advice provided in this article Revenue-based financing can be packaged into loans and other credit instruments; only focused on loans in this article Triangulated using average SBA (7) loan size as well as interview data by the author SBA (7) loan size Information only. No investment advice provided in this article Revenue-based financing can be packaged into loans and other credit instruments; only focused on loans in this article Feature Image *: Google co-founder Sergey Brin (left) came to the US at the age of 6* Feature Image Feature Image

Mispricing Opportunity: Lending to Immigrant Founders

የተሳሳተ ዋጋ መስጠት፡ ለስደተኛ መስራቾች ብድር መስጠት

Възможност за погрешно ценообразуване: Кредитиране на основатели имигранти

Špatná cena: Půjčka zakladatelům přistěhovalců

Oportunidad de fijación de precios erróneos: préstamos a fundadores inmigrantes

הזדמנות לתמחור שגוי: הלוואות למייסדי עולים

Սխալ գնագոյացման հնարավորություն. վարկավորում ներգաղթյալների հիմնադիրներին

誤った価格設定の機会：移民の創業者への融資

ໂອກາດທີ່ບໍ່ຖືກຕ້ອງ: ການໃຫ້ກູ້ຢືມແກ່ຜູ້ກໍ່ຕັ້ງຄົນເຂົ້າເມືອງ

गलत मूल्य निर्धारण गर्ने अवसर: आप्रवासी संस्थापकहरूलाई उधारो

Möjlighet för felprissättning: Utlåning till invandrargrundare

Yanlış Fiyatlandırma Fırsatı: Göçmen Kuruculara Borç Verme

错误定价的机会：向移民创始人提供贷款

The internet is full of portfolios, and getting an employer’s attention in today's marketplace can be quite a challenge. Here I have compiled a nice list of 21 awesome DEV portfolios to inspire you to build or upgrade yours. Enjoy! 1 - Sean Halpin 2 - Marc Thomas 3 - Hype4 4 - Koombea 5 - Daniel Korpai 6 - Robby Leonardi 7 - Bruno Simon 8 - Rafael Caferati 9 - Brittany Chiang 10 - Joe Rutland 11 - Jacek Jeznach 12 - Kuon Yagi 13 - Moonfarmer 14 - Titus Klein 15 - Jenny Johannesson 16 - Riccardo Zanutta 17 - J&P MEDIA LABS 18 - Animal 19 - Yul Moreau 20 - Resn 21 - Active Theory I hope you enjoyed the read! Feel free to follow me on , , , and ! Twitter LinkedIn GitHub Hashnode DEV Contact me via for more. hi@madza.dev Previously published at https://blog.madza.dev/21-awesome-dev-portfolios-for-your-inspiration

21 Best Developer Portfolio Examples

21 mejores ejemplos de cartera de desarrolladores

HONG KONG, Hong Kong, November 28th, 2024/Chainwire/--Moongate has officially launched its native token, $MGT, marking a significant milestone in the company’s mission to reshape brand-consumer engagement and redefine the value of user attention. Moongate is the first attention asset protocol for real-world activations. Launched in 2022, Moongate Protocol is actively utilized by over 3,800 brands and creators, including Binance, OKX, Token2049, EthDenver, Animoca, Wonderfruit, ComplexCon, and Sony. The protocol has empowered thousands of brands to launch smart token campaigns, driving engagement from more than 1.7 million end users. As the digital landscape continues to evolve, the $MGT token introduces a structured, incentive-based model for brands and consumers alike.￼ Designed to support real-world brand activations, loyalty programs, and consumer engagement, $MGT allows users to earn rewards through participation in token-based campaigns while brands can leverage the protocol to interact more meaningfully with their audiences. $5.2M in Funding and Upcoming Exchange Listings for $MGT To achieve this vision and further fuel growth, Moongate successfully secured over $5.2 million in total funding. This includes investments from CMCC Global, Cogitent Ventures, and Token Bay Capital, as well as public sale proceeds from multiple Tier-1 launchpads. The fundraise reflects strong market interest in Moongate Protocol and $MGT, highlighting growing recognition of Moongate’s role in the attention economy. Following the launch of the $MGT token, it is now trading on Bitget, KuCoin, Gate.io, MEXC, and PancakeSwap. Bridging Digital and Real-World Engagement Moongate’s platform empowers brands to create and distribute smart tokens, offering a streamlined solution for businesses to connect directly with users both online and offline. Through initiatives such as NFT memberships, event tickets, and token-gated benefits, Moongate facilitates real-world utilities for brands. $MGT is at the core of this ecosystem, serving as the primary medium for rewards, user incentives, and engagement tracking. “We believe that $MGT will fundamentally shift how users and brands perceive and value engagement,” said Moongate’s CEO, Jonathan Mui. “With $MGT, users gain real benefits for their interactions, while brands can access insights and audiences that reflect genuine interest and commitment.” Key Features of the $MGT Token The launch of $MGT brings multiple features to users and brands: User Staking and Rewards: Users can stake $MGT to earn incentives, receive an allocation to exclusive launches, and participate in governance, shaping the protocol’s future development.
Campaign Creation for Brands: Brands can use $MGT to create premium smart token campaigns with expanded functionalities, including an in-depth CRM, analytics, and improved discoverability.
Currency for Attention: Brands can utilize $MGT as a reward to capture eligible users’ attention and engagement. This becomes a more efficient customer acquisition channel, enabling a new paradigm where ad-spent goes directly towards the end-user (rather than any intermediaries). For more information about $MGT tokenomics, users can visit Moongate’s Medium. Community Airdrop In line with Moongate’s commitment to rewarding early supporters, the protocol will distribute a portion of the total $MGT supply through a community airdrop. The snapshot was taken on November 15, 2024, and eligible users can now claim their $MGT tokens on claim.moongate.id. What’s Next for Moongate With the launch of $MGT, Moongate is set to expand its platform features while strengthening its partnerships with both Web2 and Web3 brands. Upcoming updates include enhanced staking features, an expanded rewards marketplace, and the release of MoonPad, a launchpad for partner token campaigns. These developments aim to deepen user participation and provide brands with powerful tools to create immersive experiences for their audiences. For more information on $MGT and Moongate’s vision for the future of attention assets, users can visit Moongate’s official website. About Moongate Moongate is an attention asset protocol disrupting the $1T+ attention economy. The protocol consists of two key layers—a utility layer for brands to issue smart token campaigns for real-world engagement, and a data layer where such on-chain engagement data are monetized at scale by key stakeholders. Moongate aims to disintermediate centralized platforms to maximize brand-consumer value. It also introduces an innovative “engage-to-earn” mechanism that promotes active consumer participation for brand rewards and a share of $MGT emission. To learn more users can visit Moongate's Official Website | Twitter | LinkedIn Contact CEO Jonathan Mui Moongate contact@moongate.id This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here HONG KONG, Hong Kong, November 28th, 2024/Chainwire/--Moongate has officially launched its native token, $MGT, marking a significant milestone in the company’s mission to reshape brand-consumer engagement and redefine the value of user attention. Moongate is the first attention asset protocol for real-world activations. Launched in 2022, Moongate Protocol is actively utilized by over 3,800 brands and creators, including Binance, OKX, Token2049, EthDenver, Animoca, Wonderfruit, ComplexCon, and Sony. The protocol has empowered thousands of brands to launch smart token campaigns, driving engagement from more than 1.7 million end users. As the digital landscape continues to evolve, the $MGT token introduces a structured, incentive-based model for brands and consumers alike.￼ Designed to support real-world brand activations, loyalty programs, and consumer engagement, $MGT allows users to earn rewards through participation in token-based campaigns while brands can leverage the protocol to interact more meaningfully with their audiences. $5.2M in Funding and Upcoming Exchange Listings for $MGT To achieve this vision and further fuel growth, Moongate successfully secured over $5.2 million in total funding. This includes investments from CMCC Global, Cogitent Ventures, and Token Bay Capital, as well as public sale proceeds from multiple Tier-1 launchpads. The fundraise reflects strong market interest in Moongate Protocol and $MGT, highlighting growing recognition of Moongate’s role in the attention economy. Following the launch of the $MGT token, it is now trading on Bitget , KuCoin , Gate.io, MEXC , and PancakeSwap . Bitget Bitget KuCoin KuCoin Gate.io, Gate.io, MEXC MEXC PancakeSwap PancakeSwap Bridging Digital and Real-World Engagement Moongate’s platform empowers brands to create and distribute smart tokens, offering a streamlined solution for businesses to connect directly with users both online and offline. Through initiatives such as NFT memberships, event tickets, and token-gated benefits, Moongate facilitates real-world utilities for brands. $MGT is at the core of this ecosystem, serving as the primary medium for rewards, user incentives, and engagement tracking. “We believe that $MGT will fundamentally shift how users and brands perceive and value engagement,” said Moongate’s CEO, Jonathan Mui. “We believe that $MGT will fundamentally shift how users and brands perceive and value engagement,” said Moongate’s CEO, Jonathan Mui. “With $MGT, users gain real benefits for their interactions, while brands can access insights and audiences that reflect genuine interest and commitment.” “With $MGT, users gain real benefits for their interactions, while brands can access insights and audiences that reflect genuine interest and commitment.” Key Features of the $MGT Token The launch of $MGT brings multiple features to users and brands: User Staking and Rewards: Users can stake $MGT to earn incentives, receive an allocation to exclusive launches, and participate in governance, shaping the protocol’s future development. Campaign Creation for Brands: Brands can use $MGT to create premium smart token campaigns with expanded functionalities, including an in-depth CRM, analytics, and improved discoverability. Currency for Attention: Brands can utilize $MGT as a reward to capture eligible users’ attention and engagement. This becomes a more efficient customer acquisition channel, enabling a new paradigm where ad-spent goes directly towards the end-user (rather than any intermediaries). User Staking and Rewards: Users can stake $MGT to earn incentives, receive an allocation to exclusive launches, and participate in governance, shaping the protocol’s future development. Campaign Creation for Brands: Brands can use $MGT to create premium smart token campaigns with expanded functionalities, including an in-depth CRM, analytics, and improved discoverability. Currency for Attention: Brands can utilize $MGT as a reward to capture eligible users’ attention and engagement. This becomes a more efficient customer acquisition channel, enabling a new paradigm where ad-spent goes directly towards the end-user (rather than any intermediaries). For more information about $MGT tokenomics, users can visit Moongate’s Medium . Moongate’s Medium Moongate’s Medium Community Airdrop In line with Moongate’s commitment to rewarding early supporters, the protocol will distribute a portion of the total $MGT supply through a community airdrop. The snapshot was taken on November 15, 2024, and eligible users can now claim their $MGT tokens on claim.moongate.id . claim.moongate.id claim.moongate.id What’s Next for Moongate With the launch of $MGT, Moongate is set to expand its platform features while strengthening its partnerships with both Web2 and Web3 brands. Upcoming updates include enhanced staking features, an expanded rewards marketplace, and the release of MoonPad, a launchpad for partner token campaigns. These developments aim to deepen user participation and provide brands with powerful tools to create immersive experiences for their audiences. For more information on $MGT and Moongate’s vision for the future of attention assets, users can visit Moongate’s official website . Moongate’s official website Moongate’s official website About Moongate Moongate is an attention asset protocol disrupting the $1T+ attention economy. The protocol consists of two key layers—a utility layer for brands to issue smart token campaigns for real-world engagement, and a data layer where such on-chain engagement data are monetized at scale by key stakeholders. Moongate Moongate Moongate aims to disintermediate centralized platforms to maximize brand-consumer value. It also introduces an innovative “engage-to-earn” mechanism that promotes active consumer participation for brand rewards and a share of $MGT emission. To learn more users can visit Moongate's Official Website | Twitter | LinkedIn Official Website Official Website Twitter Twitter LinkedIn LinkedIn Contact CEO Jonathan Mui Moongate contact@moongate.id This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Moongate Launches $MGT Token To Drive New Era of Engagement In The Attention Economy

Moongate ukax $MGT Token ukaruw uñstayi, Machaq Era de Compromiso Economía de Atención Ukan Irpañataki

Moongate spouští token $MGT, aby podpořil novou éru angažovanosti v ekonomice pozornosti

Moongate lanza el token $MGT para impulsar una nueva era de participación en la economía de la atención

Moongate julkaisee $MGT Tokenin edistääkseen sitoutumisen uutta aikakautta huomiotaloudessa

Moongate lance le jeton $MGT pour ouvrir une nouvelle ère d'engagement dans l'économie de l'attention

ムーンゲート、アテンションエコノミーにおけるエンゲージメントの新時代を推進するため$MGTトークンをローンチ

Moongate-ი გამოუშვებს $MGT ტოკენს, რათა მოახდინოს ჩართულობის ახალი ერა საყურადღებო ეკონომიკაში

Moongate dia namoaka $MGT Token hitondrana ny vanim-potoana vaovaon'ny fandraisana anjara amin'ny toe-karena

ध्यान अर्थतन्त्रमा संलग्नताको नयाँ युग चलाउन मुनगेटले $MGT टोकन सुरु गर्‍यो

Moongate wprowadza token $MGT, aby rozpocząć nową erę zaangażowania w gospodarce uwagi

Moongate lanserar $MGT-token för att driva en ny era av engagemang i uppmärksamhetsekonomin

Moongate เปิดตัวโทเค็น $MGT เพื่อขับเคลื่อนยุคใหม่ของการมีส่วนร่วมในเศรษฐกิจแห่งความสนใจ

HONG KONG, Hong Kong, October 4th, 2024/Chainwire/--Moongate Protocol, an attention asset protocol disrupting the $1 trillion-plus attention economy, announces significant milestones in its expansion, the launch of its Moon Odyssey community points program, and the upcoming release of its first NFT collection, the Moongate Voyager Pass. “Moongate Protocol is an attention asset protocol revolutionizing brand-consumer engagement,” says Jonathan Mui, Founder and CEO of Moongate. Since securing a $2.7 million seed funding round earlier this year, Moongate has rapidly expanded its reach, growing the number of platform creators to over 3,500, who together have issued more than 4,500 smart token campaigns across over 40 countries. Many prominent global brands have adopted the protocol, including Binance, OKX, ComplexCon, TOKEN2049, and Wonderfruit. Overall, Moongate has facilitated over 20 million interactions among more than 1 million end-users. Building on this momentum, Moongate recently took the on-chain questing phenomenon offline with its newly developed MoonQuest platform, which it unveiled through a partnership with TOKEN2049 Singapore, the world’s largest cryptocurrency conference. By designing interactive quests throughout the TOKEN2049 venue and utilizing smart tokens to reward attendees for their participation, Moongate delivered immersive and engaging experiences while introducing many Web2 users to Web3. The activation drew in over 1,500 participants who completed more than 6,000 quests over two days, demonstrating the effectiveness of smart tokens in large-scale events. Users can learn more about Moongate's funding success here. Expected Token Generation Event and Earning Opportunities Amidst its rapid growth, there are talks of an upcoming Token Generation Event slated in the coming months. While official details are yet to be announced, speculation suggests that the event could offer new avenues for users to engage with Moongate's ecosystem. In anticipation, Moongate has launched Moon Odyssey, a community points program where participants can earn points by completing social tasks and checking into the platform daily. These points will contribute to future rewards, potentially tied to the upcoming TGE. Adding to this excitement, Moongate is also introducing its first NFT collection—the Moongate Voyager Pass. The limited collection of 6,969 NFTs will offer various benefits, with a primary feature being a guaranteed airdrop. The Moongate Voyager Pass is set to launch on October 21 this year on the OKX NFT Launchpad. Official news regarding the launch is available on its website: https://app.moongate.id/quest. About Moongate Moongate is an attention asset protocol disrupting the $1T+ attention economy. The protocol consists of two key layers—a utility layer for brands to issue smart token campaigns for real-world engagement, and a data layer where such on-chain engagement data are monetized at scale by key stakeholders. Moongate aims to disintermediate centralized platforms to maximize brand-consumer value. It also introduces an innovative “engage-to-earn” mechanism that promotes active consumer participation for brand rewards and a share of $MGT emission. To learn more users can visit Moongate's Official Website | Twitter | LinkedIn Contact CEO Jonathan Mui Moongate jon@moongate.id This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here HONG KONG, Hong Kong, October 4th, 2024/Chainwire/--Moongate Protocol, an attention asset protocol disrupting the $1 trillion-plus attention economy, announces significant milestones in its expansion, the launch of its Moon Odyssey community points program, and the upcoming release of its first NFT collection, the Moongate Voyager Pass. “Moongate Protocol is an attention asset protocol revolutionizing brand-consumer engagement,” says Jonathan Mui, Founder and CEO of Moongate. “Moongate Protocol is an attention asset protocol revolutionizing brand-consumer engagement,” says Jonathan Mui, Founder and CEO of Moongate. Since securing a $2.7 million seed funding round earlier this year, Moongate has rapidly expanded its reach, growing the number of platform creators to over 3,500, who together have issued more than 4,500 smart token campaigns across over 40 countries. Many prominent global brands have adopted the protocol, including Binance, OKX, ComplexCon, TOKEN2049, and Wonderfruit. Overall, Moongate has facilitated over 20 million interactions among more than 1 million end-users. Building on this momentum, Moongate recently took the on-chain questing phenomenon offline with its newly developed MoonQuest platform, which it unveiled through a partnership with TOKEN2049 Singapore, the world’s largest cryptocurrency conference. By designing interactive quests throughout the TOKEN2049 venue and utilizing smart tokens to reward attendees for their participation, Moongate delivered immersive and engaging experiences while introducing many Web2 users to Web3. The activation drew in over 1,500 participants who completed more than 6,000 quests over two days, demonstrating the effectiveness of smart tokens in large-scale events. Users can learn more about Moongate's funding success here . Users can learn more about Moongate's funding success here Users can learn more about Moongate's funding success here Expected Token Generation Event and Earning Opportunities Amidst its rapid growth, there are talks of an upcoming Token Generation Event slated in the coming months. While official details are yet to be announced, speculation suggests that the event could offer new avenues for users to engage with Moongate's ecosystem. In anticipation, Moongate has launched Moon Odyssey, a community points program where participants can earn points by completing social tasks and checking into the platform daily. These points will contribute to future rewards, potentially tied to the upcoming TGE. Adding to this excitement, Moongate is also introducing its first NFT collection—the Moongate Voyager Pass. The limited collection of 6,969 NFTs will offer various benefits, with a primary feature being a guaranteed airdrop. The Moongate Voyager Pass is set to launch on October 21 this year on the OKX NFT Launchpad. Official news regarding the launch is available on its website: https://app.moongate.id/quest . https://app.moongate.id/quest https://app.moongate.id/quest About Moongate Moongate is an attention asset protocol disrupting the $1T+ attention economy. The protocol consists of two key layers—a utility layer for brands to issue smart token campaigns for real-world engagement, and a data layer where such on-chain engagement data are monetized at scale by key stakeholders. Moongate Moongate Moongate aims to disintermediate centralized platforms to maximize brand-consumer value. It also introduces an innovative “engage-to-earn” mechanism that promotes active consumer participation for brand rewards and a share of $MGT emission. To learn more users can visit Moongate's Official Website | Twitter | LinkedIn Official Website Official Website Twitter Twitter LinkedIn LinkedIn Contact CEO Jonathan Mui Moongate jon@moongate.id This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Moongate Launches New Rewards Program And NFT Collection

Moongate নতুন পুরস্কার প্রোগ্রাম এবং NFT সংগ্রহ চালু করেছে

Moongate startet neues Prämienprogramm und NFT-Sammlung

Moongate lanza un nuevo programa de recompensas y una colección de NFT

Moongate lance un nouveau programme de récompenses et une collection NFT

मूनगेट ने नया रिवॉर्ड प्रोग्राम और NFT कलेक्शन लॉन्च किया

ムーンゲートが新たな報酬プログラムとNFTコレクションを開始

Moongate, 새로운 보상 프로그램 및 NFT 컬렉션 출시

Moongate lança novo programa de recompensas e coleção NFT

Moongate запускает новую программу вознаграждений и коллекцию NFT

Moongate Yeni Ödül Programı ve NFT Koleksiyonu Başlatıyor

Moongate Ra Mắt Chương Trình Phần Thưởng Mới Và Bộ Sưu Tập NFT

Moongate 推出新的奖励计划和 NFT 收藏

**SINGAPORE, Singapore, September 13th, 2024/Chainwire/--**SynFutures, the leading DeFi derivatives protocol, today announced the second edition of Borderless Summit , the first crypto event series dedicated to bridging East and West and offering global perspectives on some of the most timely topics in Web3. The summit will be held at Sofitel Singapore City Centre on September 17, 2024, during TOKEN2049 Singapore and explore the evolution of the Web3 user experience. With a diverse lineup of speakers from Base, Dragonfly Capital, 1inch, Founders Fund, Framework Ventures, Agora, and more leading Web3 organizations, Borderless Summit will offer a unique platform for diverse cross-border perspectives on trending narratives. The half-day summit will take place during the TOKEN2049 activities and feature panel discussions and a networking happy hour. Speakers include: ​​Sergej Kunz, Co-Founder at 1inch


Haseeb Qureshi, Managing Partner at Dragonfly Capital


Vance Spencer, Co-Founder at Framework Ventures


Nick Matthew, Investor at Standard Crypto


Eugene Ng, Co-Founder at DWF Labs/OpenEden


Eric Brown, Senior Developer Advocate at Base


Simon Baksys, VP of BD at LayerZero Labs


Mr. Block, Core Team at Puffer & Curve.fi


Joey Anthony, Head of Infrastructure, Monad


Jocy, Founding Partner, IOSG Ventures


Mark Lee, Partner and CMO at SynFutures


Ryan Kim, Founding Partner at Hashed


Joey Krug, Partner at Founders Fund


Nick van Eck, Co-Founder and CEO at Agora


Mike Silagadze, CEO at Ether.fi


Maarten Henskens, Head of Growth at Soneium


Shuyao Kong, Co-Founder at MegaETH


Paul Frambot, Co-Founder and CEO at Morpho Labs


Antonio Garcia-Martinez, CEO & Founder, Spindl


Irene Zhao of Asianmom


Chris Carapola, Co-Founder and CEO at Curvance


TN, Founder at Pendle


Jeff Liu, Co-Founder and CEO at Fuzzland Inc


Tigran Bolshoi, Co-founder, Kinetex Network


Jon Jones, Co-Founder & CBO at Supra


Fred Hsu, CEO & Co-Founder, D3


Uwe Cerron, Core Contributor, Convergence "We are thrilled to host Borderless Summit in Singapore during one of the biggest Web3 conferences of the year," said Rachel Lin, co-founder and CEO at SynFutures. “This event represents a unique opportunity to not only explore one of the biggest trends in Web3 but gather some of the most brilliant minds across the world together in one room.” Borderless Summit will be held on Tuesday, September, from 1:30 to 7:30 PM GMT+8. Registration will begin at 1:30 PM. For the full agenda, see the event page. The event is organized by SynFutures. Fuzzland is a Diamond Sponsor. D3, Kinetex Network, and Supra are Gold Sponsors, and zkLink, Zomma Protocol, and Yay! are Silver Sponsors. Media partners include ​Wu Blockchain, CoinPost, BlockBeats, Token Post, Xangle, Traders Guild, PANews, Beincrypto, Foresight News, Cryptonews, Moongate, Talkchain Malaysia, Cointelegram, Coindesk Indonesia, Cointelegraph Japan, The Coin Republic, CryptoWesearch, and Bitcoin Addict. Registration and Additional Information To register for Borderless Summit 2024 and for more details about the event, visit https://lu.ma/borderlesssummit2. About Borderless Summit Borderless Summit is the first crypto event series dedicated to bridging East and West. Designed to help founders and builders better navigate global markets, Borderless Summit offers a unique platform for diverse cross-border perspectives on trending narratives in Web3. For more information, go to https://lu.ma/borderlesssummit2. About SynFutures SynFutures is a decentralized perpetual futures protocol that facilitates open and transparent trading on any assets and listings instantly. The V3 Oyster AMM launched the industry's first-ever unified AMM and onchain order book model. Backers include Tier 1 Web3 institutional investors Pantera Capital, Polychain Capital, Susquehanna International Group (SIG), Dragonfly Capital, Standard Crypto, and Framework Ventures, and the team has extensive experience at global financial institutions, fintech companies and blockchain technology companies such as Alipay, Bitmain, Credit Suisse, Deutsche Bank, Matrixport, and Nomura Securities. Contact CMO Mark Lee SynFutures mark.lee@synfutures.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **SINGAPORE, Singapore, September 13th, 2024/Chainwire/--**SynFutures, the leading DeFi derivatives protocol, today announced the second edition of Borderless Summit , the first crypto event series dedicated to bridging East and West and offering global perspectives on some of the most timely topics in Web3. The summit will be held at Sofitel Singapore City Centre on September 17, 2024, during TOKEN2049 Singapore and explore the evolution of the Web3 user experience. With a diverse lineup of speakers from Base, Dragonfly Capital, 1inch, Founders Fund, Framework Ventures, Agora, and more leading Web3 organizations, Borderless Summit will offer a unique platform for diverse cross-border perspectives on trending narratives. The half-day summit will take place during the TOKEN2049 activities and feature panel discussions and a networking happy hour. Speakers include: ​​Sergej Kunz, Co-Founder at 1inch Haseeb Qureshi, Managing Partner at Dragonfly Capital Vance Spencer, Co-Founder at Framework Ventures Nick Matthew, Investor at Standard Crypto Eugene Ng, Co-Founder at DWF Labs/OpenEden Eric Brown, Senior Developer Advocate at Base Simon Baksys, VP of BD at LayerZero Labs Mr. Block, Core Team at Puffer & Curve.fi Joey Anthony, Head of Infrastructure, Monad Jocy, Founding Partner, IOSG Ventures Mark Lee, Partner and CMO at SynFutures Ryan Kim, Founding Partner at Hashed Joey Krug, Partner at Founders Fund Nick van Eck, Co-Founder and CEO at Agora Mike Silagadze, CEO at Ether.fi Maarten Henskens, Head of Growth at Soneium Shuyao Kong, Co-Founder at MegaETH Paul Frambot, Co-Founder and CEO at Morpho Labs Antonio Garcia-Martinez, CEO & Founder, Spindl Irene Zhao of Asianmom Chris Carapola, Co-Founder and CEO at Curvance TN, Founder at Pendle Jeff Liu, Co-Founder and CEO at Fuzzland Inc Tigran Bolshoi, Co-founder, Kinetex Network Jon Jones, Co-Founder & CBO at Supra Fred Hsu, CEO & Co-Founder, D3 Uwe Cerron, Core Contributor, Convergence ​​Sergej Kunz, Co-Founder at 1inch ​​Sergej Kunz, Co-Founder at 1inch Haseeb Qureshi, Managing Partner at Dragonfly Capital Haseeb Qureshi, Managing Partner at Dragonfly Capital Vance Spencer, Co-Founder at Framework Ventures Vance Spencer, Co-Founder at Framework Ventures Nick Matthew, Investor at Standard Crypto Nick Matthew, Investor at Standard Crypto Eugene Ng, Co-Founder at DWF Labs/OpenEden Eugene Ng, Co-Founder at DWF Labs/OpenEden Eric Brown, Senior Developer Advocate at Base Eric Brown, Senior Developer Advocate at Base Simon Baksys, VP of BD at LayerZero Labs Simon Baksys, VP of BD at LayerZero Labs Mr. Block, Core Team at Puffer & Curve.fi Mr. Block, Core Team at Puffer & Curve.fi Joey Anthony, Head of Infrastructure, Monad Joey Anthony, Head of Infrastructure, Monad Jocy, Founding Partner, IOSG Ventures Jocy, Founding Partner, IOSG Ventures Mark Lee, Partner and CMO at SynFutures Mark Lee, Partner and CMO at SynFutures Ryan Kim, Founding Partner at Hashed Ryan Kim, Founding Partner at Hashed Joey Krug, Partner at Founders Fund Joey Krug, Partner at Founders Fund Nick van Eck, Co-Founder and CEO at Agora Nick van Eck, Co-Founder and CEO at Agora Mike Silagadze, CEO at Ether.fi Mike Silagadze, CEO at Ether.fi Maarten Henskens, Head of Growth at Soneium Maarten Henskens, Head of Growth at Soneium Shuyao Kong, Co-Founder at MegaETH Shuyao Kong, Co-Founder at MegaETH Paul Frambot, Co-Founder and CEO at Morpho Labs Paul Frambot, Co-Founder and CEO at Morpho Labs Antonio Garcia-Martinez, CEO & Founder, Spindl Antonio Garcia-Martinez, CEO & Founder, Spindl Irene Zhao of Asianmom Irene Zhao of Asianmom Chris Carapola, Co-Founder and CEO at Curvance Chris Carapola, Co-Founder and CEO at Curvance TN, Founder at Pendle TN, Founder at Pendle Jeff Liu, Co-Founder and CEO at Fuzzland Inc Jeff Liu, Co-Founder and CEO at Fuzzland Inc Tigran Bolshoi, Co-founder, Kinetex Network Tigran Bolshoi, Co-founder, Kinetex Network Jon Jones, Co-Founder & CBO at Supra Jon Jones, Co-Founder & CBO at Supra Fred Hsu, CEO & Co-Founder, D3 Fred Hsu, CEO & Co-Founder, D3 Uwe Cerron, Core Contributor, Convergence Uwe Cerron, Core Contributor, Convergence "We are thrilled to host Borderless Summit in Singapore during one of the biggest Web3 conferences of the year," said Rachel Lin, co-founder and CEO at SynFutures. “This event represents a unique opportunity to not only explore one of the biggest trends in Web3 but gather some of the most brilliant minds across the world together in one room.” "We are thrilled to host Borderless Summit in Singapore during one of the biggest Web3 conferences of the year," said Rachel Lin, co-founder and CEO at SynFutures. “This event represents a unique opportunity to not only explore one of the biggest trends in Web3 but gather some of the most brilliant minds across the world together in one room.” Borderless Summit will be held on Tuesday, September, from 1:30 to 7:30 PM GMT+8. Registration will begin at 1:30 PM. For the full agenda, see the event page . event page event page The event is organized by SynFutures. Fuzzland is a Diamond Sponsor. D3, Kinetex Network, and Supra are Gold Sponsors, and zkLink, Zomma Protocol, and Yay! are Silver Sponsors. Media partners include ​Wu Blockchain, CoinPost, BlockBeats, Token Post, Xangle, Traders Guild, PANews, Beincrypto, Foresight News, Cryptonews, Moongate, Talkchain Malaysia, Cointelegram, Coindesk Indonesia, Cointelegraph Japan, The Coin Republic, CryptoWesearch, and Bitcoin Addict. Registration and Additional Information To register for Borderless Summit 2024 and for more details about the event, visit https://lu.ma/borderlesssummit2 . https://lu.ma/borderlesssummit2 https://lu.ma/borderlesssummit2 About Borderless Summit Borderless Summit is the first crypto event series dedicated to bridging East and West. Designed to help founders and builders better navigate global markets, Borderless Summit offers a unique platform for diverse cross-border perspectives on trending narratives in Web3. For more information, go to https://lu.ma/borderlesssummit2 . https://lu.ma/borderlesssummit2 https://lu.ma/borderlesssummit2 About SynFutures SynFutures is a decentralized perpetual futures protocol that facilitates open and transparent trading on any assets and listings instantly. The V3 Oyster AMM launched the industry's first-ever unified AMM and onchain order book model. Backers include Tier 1 Web3 institutional investors Pantera Capital, Polychain Capital, Susquehanna International Group (SIG), Dragonfly Capital, Standard Crypto, and Framework Ventures, and the team has extensive experience at global financial institutions, fintech companies and blockchain technology companies such as Alipay, Bitmain, Credit Suisse, Deutsche Bank, Matrixport, and Nomura Securities. Contact CMO Mark Lee SynFutures mark.lee@synfutures.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Borderless Summit To Explore The Era Of Consumer-First Web3 During TOKEN2049 Singapore

قمة بلا حدود لاستكشاف عصر Web3 الذي يركز على المستهلك خلال TOKEN2049 سنغافورة

Borderless Summit za istraživanje ere Consumer-First Web3 tokom TOKEN2049 Singapur

La cumbre sin fronteras explorará la era de la Web3 centrada en el consumidor durante TOKEN2049 Singapur

Mugarik gabeko gailurra Kontsumitzaileen lehen web 3aren garaia aztertzeko TOKEN2049 Singapurren zehar

Անսահման գագաթնաժողով՝ ուսումնասիրելու սպառողների առաջին վեբի դարաշրջանը TOKEN2049 Սինգապուրի ժամանակ

ボーダーレスサミット、TOKEN2049シンガポールで消費者第一のWeb3時代を探る

Vovonana tsy misy sisintany hijerena ny vanim-potoanan'ny mpanjifa-voalohany Web3 mandritra ny TOKEN2049 Singapore

TOKEN2049 Сингапурын үеэр хэрэглэгчийн анхны вэб3-ын эрин үеийг судлах хил хязгааргүй дээд хэмжээний уулзалт

Cumbre Sin Fronteras Explorar La Era De Consumidor-Primero Web3 TOKEN2049 Singapur Kachkaptin

සිංගප්පූරුවේ TOKEN2049 අතරතුර පාරිභෝගික-පළමු Web3 යුගය ගවේෂණය කිරීමට දේශසීමා රහිත සමුළුව

Саміт без кордонів, щоб дослідити еру Consumer-First Web3 під час TOKEN2049 Сінгапур

TOKEN2049 سنگاپور کے دوران کنزیومر فرسٹ ویب 3 کے دور کو دریافت کرنے کے لیے بارڈر لیس سمٹ

Authors:
(1) Ronen Eldan, Microsoft Research (email: roneneldan@microsoft.com);
(2) Mark Russinovich, Microsoft Azure and Both authors contributed equally to this work, (email: mark.russinovich@microsoft.com). Table of Links Abstract and Introduction
Description of our technique
Evaluation methodology
Results
Conclusion, Acknowledgment, and References
Appendix 5 Conclusion The ambitious endeavor of teaching a Large Language Model (LLM) to selectively forget, or ”unlearn”, is a testament to the nuanced complexities inherent in the world of artificial intelligence and machine learning. Widely regarded as a daunting task, any attempt at enabling such a functionality in LLMs stands at the vanguard of innovative solutions, and in this light, our proof of concept arguably underscores progress. Firstly, our research demonstrates that unlearning, though challenging, is not an insurmountable task, as the positive outcomes in our experiments with the Llama2-7b model suggest. Yet, this achievement must be contextualized with prudence. Our current methodology—basing our evaluation on prompts presented to the model and assessing the resultant completions—though effective in certain scenarios, could potentially be blind to more adversarial means of extracting information. It’s conceivable that non-traditional or intricate methods, such as delving into token probability distributions, might inadvertently reveal the model’s latent familiarity with unlearned content. Diving deeper into the potential generality of our technique, a pertinent observation emerges when considering the unique attributes of the Harry Potter series. The books are replete with idiosyncratic expressions and distinctive names—traits that, in hindsight, may have abetted our unlearning strategy. The pronounced presence of Harry Potter themes across the training data of many LLMs further compounds the challenge. Given such widespread representation, even the slightest hint in a prompt might stir a cascade of related completions, underscoring the depth of memory ingrained in the model. A nuance of our methodology involves a reliance on GPT-4’s existing knowledge of the Harry Potter universe. To detect specific anchored terms and devise generic counterparts, the expertise of GPT-4 proved useful. This raises the question whether our technique achieve similar efficacy when stripped of such vast prior knowledge. Preliminary experiments show that entity extraction can still be effective when this knowledge is absent, and we speculate that the lack of familiarity with idiosyncratic expressions can be addressed with simple n-gram frequency analysis but we leave a more thorough study for future work. Extending our approach to other types of content, particularly non-fiction or textbooks, presents its own set of challenges. Unlike the fictional universe of Harry Potter, non-fiction content will not possess the same density of unique terms or phrases. Furthermore, non-fictional texts often embed higher-level constructs such as ideas, concepts, or cultural perspectives. It remains uncertain to what extent our technique can effectively address and unlearn these more abstract elements. This would clearly necessitate adaptations of our technique. In conclusion, while our technique offers a promising start, its applicability across various content types remains to be thoroughly tested. The presented approach offers a foundation, but further research is needed to refine and extend the methodology for broader unlearning tasks in LLMs. Acknowledgement The authors would like to thank Yanan Cai for helping to configure and manage the Azure GPU VMs used for this work. References [BHT+19] Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Y Chai, Mirella Lapata, Angeliki Lazaridou, Ryan J Maynez, Piyush Narang, et al. Piqa: Reasoning about physical commonsense in natural language. arXiv preprint arXiv:1911.11641, 2019. [CLC+19] Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. Boolq: Exploring the surprising difficulty of natural yes/no questions. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 2924–2936, 2019. [GTB+21] Leo Gao, Jonathan Tow, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Kyle McDonell, Niklas Muennighoff, Jason Phang, Laria Reynolds, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou. A framework for few-shot language model evaluation, September 2021. [JLZ+22] Yiwen Jiang, Shenglong Liu, Tao Zhao, Wei Li, and Xianzhou Gao. Machine unlearning survey. In Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), volume 12500, pages 1596–1603. SPIE, 2022. [JYY+22] Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, and Minjoon Seo. Knowledge unlearning for mitigating privacy risks in language models. arXiv preprint arXiv:2210.01504, 2022. [MCKS18] Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. Can a suit of armor conduct electricity? a new dataset for open book question answering. arXiv preprint arXiv:1809.02789, 2018. [NHN+22] Thanh Tam Nguyen, Thanh Trung Huynh, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, and Quoc Viet Hung Nguyen. A survey of machine unlearning. arXiv preprint arXiv:2209.02299, 2022. [Row07] J.K. Rowling. The Harry Potter Series. Bloomsbury, 1997-2007. Comprising: Harry Potter and the Philosopher’s Stone; Harry Potter and the Chamber of Secrets; Harry Potter and the Prisoner of Azkaban; Harry Potter and the Goblet of Fire; Harry Potter and the Order of the Phoenix; Harry Potter and the Half-Blood Prince; Harry Potter and the Deathly Hallows. [SLBBC19] Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. Winogrande: An adversarial winograd schema challenge at scale. arXiv preprint arXiv:1907.10641, 2019. WCY+23] Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, and Hongzhi Yin. Kga: A general machine unlearning framework based on knowledge gap alignment. arXiv preprint arXiv:2305.06535, 2023. [YBS19] Vikas Yadav, Steven Bethard, and Mihai Surdeanu. Quick and (not so) dirty: Unsupervised selection of justification sentences for multi-hop question answering. arXiv preprint arXiv:1911.07176, 2019. [ZFBH+23] Dawen Zhang, Pamela Finckenberg-Broman, Thong Hoang, Shidong Pan, Zhenchang Xing, Mark Staples, and Xiwei Xu. Right to be forgotten in the era of large language models: Implications, challenges, and solutions. arXiv preprint arXiv:2307.03941, 2023. [ZHB+19] Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4791–4800, 2019. [ZNIS23] Haibo Zhang, Toru Nakamura, Takamasa Isohara, and Kouichi Sakurai. A review on machine unlearning. SN Computer Science, 4(4):337, 2023. This paper is available on arxiv under CC 4.0 license. Authors: (1) Ronen Eldan, Microsoft Research (email: roneneldan@microsoft.com); (2) Mark Russinovich, Microsoft Azure and Both authors contributed equally to this work, (email: mark.russinovich@microsoft.com). Authors: Authors: (1) Ronen Eldan, Microsoft Research (email: roneneldan@microsoft.com); (2) Mark Russinovich, Microsoft Azure and Both authors contributed equally to this work, (email: mark.russinovich@microsoft.com). Table of Links Abstract and Introduction Description of our technique Evaluation methodology Results Conclusion, Acknowledgment, and References Appendix Abstract and Introduction Abstract and Introduction Description of our technique Description of our technique Evaluation methodology Evaluation methodology Results Results Conclusion, Acknowledgment, and References Conclusion, Acknowledgment, and References Appendix Appendix 5 Conclusion The ambitious endeavor of teaching a Large Language Model (LLM) to selectively forget, or ”unlearn”, is a testament to the nuanced complexities inherent in the world of artificial intelligence and machine learning. Widely regarded as a daunting task, any attempt at enabling such a functionality in LLMs stands at the vanguard of innovative solutions, and in this light, our proof of concept arguably underscores progress. Firstly, our research demonstrates that unlearning, though challenging, is not an insurmountable task, as the positive outcomes in our experiments with the Llama2-7b model suggest. Yet, this achievement must be contextualized with prudence. Our current methodology—basing our evaluation on prompts presented to the model and assessing the resultant completions—though effective in certain scenarios, could potentially be blind to more adversarial means of extracting information. It’s conceivable that non-traditional or intricate methods, such as delving into token probability distributions, might inadvertently reveal the model’s latent familiarity with unlearned content. Diving deeper into the potential generality of our technique, a pertinent observation emerges when considering the unique attributes of the Harry Potter series. The books are replete with idiosyncratic expressions and distinctive names—traits that, in hindsight, may have abetted our unlearning strategy. The pronounced presence of Harry Potter themes across the training data of many LLMs further compounds the challenge. Given such widespread representation, even the slightest hint in a prompt might stir a cascade of related completions, underscoring the depth of memory ingrained in the model. A nuance of our methodology involves a reliance on GPT-4’s existing knowledge of the Harry Potter universe. To detect specific anchored terms and devise generic counterparts, the expertise of GPT-4 proved useful. This raises the question whether our technique achieve similar efficacy when stripped of such vast prior knowledge. Preliminary experiments show that entity extraction can still be effective when this knowledge is absent, and we speculate that the lack of familiarity with idiosyncratic expressions can be addressed with simple n-gram frequency analysis but we leave a more thorough study for future work. Extending our approach to other types of content, particularly non-fiction or textbooks, presents its own set of challenges. Unlike the fictional universe of Harry Potter, non-fiction content will not possess the same density of unique terms or phrases. Furthermore, non-fictional texts often embed higher-level constructs such as ideas, concepts, or cultural perspectives. It remains uncertain to what extent our technique can effectively address and unlearn these more abstract elements. This would clearly necessitate adaptations of our technique. In conclusion, while our technique offers a promising start, its applicability across various content types remains to be thoroughly tested. The presented approach offers a foundation, but further research is needed to refine and extend the methodology for broader unlearning tasks in LLMs. Acknowledgement The authors would like to thank Yanan Cai for helping to configure and manage the Azure GPU VMs used for this work. References [BHT+19] Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Y Chai, Mirella Lapata, Angeliki Lazaridou, Ryan J Maynez, Piyush Narang, et al. Piqa: Reasoning about physical commonsense in natural language. arXiv preprint arXiv:1911.11641, 2019. [CLC+19] Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. Boolq: Exploring the surprising difficulty of natural yes/no questions. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 2924–2936, 2019. [GTB+21] Leo Gao, Jonathan Tow, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Kyle McDonell, Niklas Muennighoff, Jason Phang, Laria Reynolds, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou. A framework for few-shot language model evaluation, September 2021. [JLZ+22] Yiwen Jiang, Shenglong Liu, Tao Zhao, Wei Li, and Xianzhou Gao. Machine unlearning survey. In Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), volume 12500, pages 1596–1603. SPIE, 2022. [JYY+22] Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, and Minjoon Seo. Knowledge unlearning for mitigating privacy risks in language models. arXiv preprint arXiv:2210.01504, 2022. [MCKS18] Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. Can a suit of armor conduct electricity? a new dataset for open book question answering. arXiv preprint arXiv:1809.02789, 2018. [NHN+22] Thanh Tam Nguyen, Thanh Trung Huynh, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, and Quoc Viet Hung Nguyen. A survey of machine unlearning. arXiv preprint arXiv:2209.02299, 2022. [Row07] J.K. Rowling. The Harry Potter Series. Bloomsbury, 1997-2007. Comprising: Harry Potter and the Philosopher’s Stone; Harry Potter and the Chamber of Secrets; Harry Potter and the Prisoner of Azkaban; Harry Potter and the Goblet of Fire; Harry Potter and the Order of the Phoenix; Harry Potter and the Half-Blood Prince; Harry Potter and the Deathly Hallows. [SLBBC19] Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. Winogrande: An adversarial winograd schema challenge at scale. arXiv preprint arXiv:1907.10641, 2019. WCY+23] Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, and Hongzhi Yin. Kga: A general machine unlearning framework based on knowledge gap alignment. arXiv preprint arXiv:2305.06535, 2023. [YBS19] Vikas Yadav, Steven Bethard, and Mihai Surdeanu. Quick and (not so) dirty: Unsupervised selection of justification sentences for multi-hop question answering. arXiv preprint arXiv:1911.07176, 2019. [ZFBH+23] Dawen Zhang, Pamela Finckenberg-Broman, Thong Hoang, Shidong Pan, Zhenchang Xing, Mark Staples, and Xiwei Xu. Right to be forgotten in the era of large language models: Implications, challenges, and solutions. arXiv preprint arXiv:2307.03941, 2023. [ZHB+19] Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4791–4800, 2019. [ZNIS23] Haibo Zhang, Toru Nakamura, Takamasa Isohara, and Kouichi Sakurai. A review on machine unlearning. SN Computer Science, 4(4):337, 2023. 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

Who’s Harry Potter? Approximate Unlearning in LLMs: Conclusion, Acknowledgment, and References

NEW YORK, New York, May 7th, 2024/Chainwire/-- Spectral is excited to announce its participation in Hugging Face's Expert Support Program. Spectral is collaborating with deep learning experts from Hugging Face to advance open-source models, datasets, and applications for the Onchain Agent Economy. How To Use Hugging Face Hugging Face plays a critical role across Spectral's organization. Through the Expert Support Program, Spectral regularly meets with the Hugging Face team to plan new use cases, strategize dataset construction, and develop training strategies. Earlier this year, Spectral launched Syntax, which is composed of a fine-tuned LLM orchestrator that routes queries between several tools, including search, Foundry, and an open-source model to generate Solidity code. Building Syntax required custom datasets for both finetuning and RAG, an original Solidity evaluation dataset written by elite smart contract developers, and experimentation across a wide range of open and closed-source models. Spectral's approach to dataset preparation, training, routing, and evaluation has drastically improved during this process, largely due to help from Hugging Face experts. Regular discussions on Spectral's approach mean that the company always receives impartial feedback on its decisions and can reevaluate its strategy as needed. This was important for both the finetuning and evaluation steps, which have now gone through several rounds of improvement thanks to the Hugging Face team. Spectral also relies on Hugging Face for inferences in production through dedicated Inference Endpoints. The fully managed infrastructure allows Spectral to iterate on new models quickly, easily update container and hardware configurations, autoscale with demand, and keep production costs low. Over the coming months, Spectral is excited to continue to open-source its work with onchain datasets and models that interact onchain through Hugging Face. Users can view Spectral's training dataset for the credit scoring challenge and follow its progress here. The Onchain Agent Economy Syntax is pioneering the accessible onchain Agent Economy, inviting users to select agents tailored for their specific tasks. Users can either interact with the foundational agent to generate solidity code or opt for one of the specialized agents, each adept in distinct tasks. For example, we recently launched Syntax MoonMaker, an agent that launches a memecoin project end to end and are soon launching Syntax- TestMachine, an agent that detects vulnerabilities in your smart contracts. Many such agents are currently in production, and upcoming releases of our product will allow users to create their own agents and monetize them on the Syntax network. This system relies on a vast suite of functions available to language models, open-source models for tasks like classification and image generation, fast and reliable blockchain infrastructure, and a trustless system to execute and verify each step. To solve these problems, we've begun developing the Inferchain, optimized to serve the rapidly growing demand for agents and verifiable inferences. Hugging Face Users Joining The Onchain AI Community The importance of open collaboration cannot be overstated. Like many other projects, Spectral would not exist without the work of open-source contributors. Spectral is greatly indebted to everyone who makes this work possible and believes this positive impact should be recognized. As part of this engagement, Spectral is focusing specifically on users powering the AI community. The top individual and small organization contributors on Hugging Face, measured by likes and downloads of their models and datasets, are eligible to register to claim a share of SPEC tokens starting the week of May 6th. Users can check eligibility by signing in with their Hugging Face account here. A snapshot of activity was taken last month, and eligible users will not need an existing wallet to claim. This airdrop is designed to recognize users for their critical work and enable new functionality for the next generation of AI tools. Criteria Spectral reviewed all individual contributors from organizations with less than 10 members that published models or datasets. From these, Spectral took a combined measure of activity from likes and downloads for both models and datasets. Then, Spectral identified the users with the most combined activity from both model and dataset publishers (11298 in both categories) which resulted in a final list of 20,004 unique huggingface users. Spectral is looking forward to engaging further with the open-source community and building the future of AI x web3! https://claims.spectrallabs.xyz/ About Spectral Spectral, a pioneer of the agent economy behind Syntax, is at the forefront of integrating AI with blockchain to democratize development in Web3. Spectral's mission is to simplify the creation and deployment of decentralized applications through autonomous Onchain Agents. Syntax, Spectral’s flagship product, translates natural language into Solidity code, enabling both novices and experts to build on the blockchain effortlessly. With a commitment to transparency and user empowerment, Spectral is shaping a future where anyone can participate in the blockchain revolution. Join Spectral in making this vision a reality and explore the potential of autonomous agents. For more information, visit https://spectrallabs.xyz. For more information, users can follow Spectral on Twitter and Discord. Contact Spectral Labs Team contact@spectral.finance This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. NEW YORK, New York, May 7th, 2024/Chainwire/-- Spectral is excited to announce its participation in Hugging Face's Expert Support Program. Spectral is collaborating with deep learning experts from Hugging Face to advance open-source models, datasets, and applications for the Onchain Agent Economy. How To Use Hugging Face Hugging Face plays a critical role across Spectral's organization. Through the Expert Support Program, Spectral regularly meets with the Hugging Face team to plan new use cases, strategize dataset construction, and develop training strategies. Earlier this year, Spectral launched Syntax, which is composed of a fine-tuned LLM orchestrator that routes queries between several tools, including search, Foundry , and an open-source model to generate Solidity code. Foundry Foundry an open-source model an open-source model Building Syntax required custom datasets for both finetuning and RAG, an original Solidity evaluation dataset written by elite smart contract developers, and experimentation across a wide range of open and closed-source models. Spectral's approach to dataset preparation, training, routing, and evaluation has drastically improved during this process, largely due to help from Hugging Face experts. Regular discussions on Spectral's approach mean that the company always receives impartial feedback on its decisions and can reevaluate its strategy as needed. This was important for both the finetuning and evaluation steps, which have now gone through several rounds of improvement thanks to the Hugging Face team. Spectral also relies on Hugging Face for inferences in production through dedicated Inference Endpoints. The fully managed infrastructure allows Spectral to iterate on new models quickly, easily update container and hardware configurations, autoscale with demand, and keep production costs low. Over the coming months, Spectral is excited to continue to open-source its work with onchain datasets and models that interact onchain through Hugging Face. Users can view Spectral's training dataset for the credit scoring challenge and follow its progress here . here here The Onchain Agent Economy Syntax is pioneering the accessible onchain Agent Economy, inviting users to select agents tailored for their specific tasks. Users can either interact with the foundational agent to generate solidity code or opt for one of the specialized agents, each adept in distinct tasks. For example, we recently launched Syntax MoonMaker, an agent that launches a memecoin project end to end and are soon launching Syntax- TestMachine, an agent that detects vulnerabilities in your smart contracts. Many such agents are currently in production, and upcoming releases of our product will allow users to create their own agents and monetize them on the Syntax network. This system relies on a vast suite of functions available to language models, open-source models for tasks like classification and image generation, fast and reliable blockchain infrastructure, and a trustless system to execute and verify each step. To solve these problems, we've begun developing the Inferchain, optimized to serve the rapidly growing demand for agents and verifiable inferences. Hugging Face Users Joining The Onchain AI Community The importance of open collaboration cannot be overstated. Like many other projects, Spectral would not exist without the work of open-source contributors. Spectral is greatly indebted to everyone who makes this work possible and believes this positive impact should be recognized. As part of this engagement, Spectral is focusing specifically on users powering the AI community. The top individual and small organization contributors on Hugging Face, measured by likes and downloads of their models and datasets, are eligible to register to claim a share of SPEC tokens starting the week of May 6th. Users can check eligibility by signing in with their Hugging Face account here . here here A snapshot of activity was taken last month, and eligible users will not need an existing wallet to claim. This airdrop is designed to recognize users for their critical work and enable new functionality for the next generation of AI tools. Criteria Spectral reviewed all individual contributors from organizations with less than 10 members that published models or datasets. From these, Spectral took a combined measure of activity from likes and downloads for both models and datasets. Then, Spectral identified the users with the most combined activity from both model and dataset publishers (11298 in both categories) which resulted in a final list of 20,004 unique huggingface users. Spectral is looking forward to engaging further with the open-source community and building the future of AI x web3! https://claims.spectrallabs.xyz/ https://claims.spectrallabs.xyz/ https://claims.spectrallabs.xyz/ About Spectral Spectral , a pioneer of the agent economy behind Syntax, is at the forefront of integrating AI with blockchain to democratize development in Web3. Spectral's mission is to simplify the creation and deployment of decentralized applications through autonomous Onchain Agents. Spectral Spectral Syntax, Spectral’s flagship product, translates natural language into Solidity code, enabling both novices and experts to build on the blockchain effortlessly. With a commitment to transparency and user empowerment, Spectral is shaping a future where anyone can participate in the blockchain revolution. Join Spectral in making this vision a reality and explore the potential of autonomous agents. For more information, visit https://spectrallabs.xyz . For more information, users can follow Spectral on Twitter and Discord . https://spectrallabs.xyz Twitter Twitter Discord Discord Contact Spectral Labs Team contact@spectral.finance This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Spectral Labs Joins Hugging Face’s ESP Program: Advancing The Onchain x Open-Source AI Community

স্পেকট্রাল ল্যাবগুলি আলিঙ্গন মুখের ইএসপি প্রোগ্রামে যোগ দেয়: অনচেইন এক্স ওপেন-সোর্স এআই সম্প্রদায়কে এগিয়ে নিয়ে যাওয়া

Spectral Labs nimmt am ESP-Programm von Hugging Face teil: Förderung der Onchain x Open-Source-KI-Community

Spectral Labs se une al programa ESP de Hugging Face: avanzando en la comunidad de IA de código abierto Onchain x

Spectral Labs rejoint le programme ESP de Hugging Face : faire progresser la communauté d'IA Onchain x Open-Source

स्पेक्ट्रल लैब्स हगिंग फेस के ईएसपी कार्यक्रम में शामिल हुई: ऑनचेन एक्स ओपन-सोर्स एआई समुदाय को आगे बढ़ाना

Spectral Labs が Hugging Face の ESP プログラムに参加: オンチェーン x オープンソース AI コミュニティの発展

Spectral Labs, Hugging Face의 ESP 프로그램에 합류: Onchain x 오픈 소스 AI 커뮤니티 발전

Spectral Labs junta-se ao programa ESP da Hugging Face: Avançando a comunidade Onchain x Open-Source AI

Spectral Labs присоединяется к программе ESP Hugging Face: развитие сообщества искусственного интеллекта с открытым исходным кодом Onchain x

Spectral Labs, Hugging Face'in ESP Programına Katılıyor: Onchain x Açık Kaynak Yapay Zeka Topluluğunu Geliştirme

Spectral Labs tham gia chương trình ESP của Hugging Face: Thúc đẩy cộng đồng AI mã nguồn mở Onchain x

Spectral Labs 加入 Hugging Face 的 ESP 计划：推进 Onchain x 开源 AI 社区

This paper is under CC 4.0 license. available on arxiv Authors: (1) Joel Jang, CarperAI,University of Washington & Allen Institute for AI; (2) Seungone Kim, KAIST AI; (3) Yizhong Wang, University of Washington; (4) Jack Hessel, University of Washington; (5) Luke Zettlemoyer, Aleph Alpha; (6) Hannaneh Hajishirzi, University of Washington & Allen Institute for AI; (7) Yejin Choi, UC San Diego. 5 CONCLUSION Previous work has shown that adapting LLMs with RLHF helps them generate outputs that are preferred by humans over the supervised fine-tuned counterpart. However, recent work has also pointed out that simply training LLMs to abide by the preference of the general may result in ignoring individual preferences and values. In this work, we provide the first steps to tackle this issue by proposing Reinforcement Learning from Personalized Human Feedback as a multi-objective problem so that LLMs can be aligned to follow conflicting preferences. We propose a promising method called P-SOUPS that is able to composite models trained on single objectives on the fly during inference. We also highlight the scalability of P-SOUPS by showing that it scales linearly, instead of exponentially like the MORL baseline, with regards to the number of new preferences, which is required to provide true personalization to individual users. ACKNOWLEDGMENTS Thanks to Minyoung Hwang, Sungdong Kim, Tim Dettmers, Yoonjoo Lee, and Margaret Li for helpful feedback and discussion. REFERENCES Xiang Ao, Xiting Wang, Ling Luo, Ying Qiao, Qing He, and Xing Xie. PENS: A dataset and generic framework for personalized news headline generation. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 82–92, Online, August 2021. Association for Computational Linguistics. doi: 10.18653/v1/2021.acl-long.7. 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Judging llm-as-a-judge with mt-bench and chatbot arena. arXiv preprint arXiv:2306.05685, 2023. Yinhe Zheng, Guanyi Chen, Minlie Huang, Song Liu, and Xuan Zhu. Personalized dialogue generation with diversified traits. arXiv preprint arXiv:1901.09672, 2019. Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving. Fine-tuning language models from human preferences. arXiv preprint arXiv:1909.08593, 2019. A DETAILS OF EVALUATION SETUP We use a modified version of the GPT4 annotation prompt used by Dubois et al. (2023). We modify the criteria to perform the pairwise evaluation from general to a single preference dimension. We also provide 3 demonstrations: one scenario where there is a tie because both responses do not contain any notion of the preference (e.g. both responses do not show any signs of friendliness), one scenario where there is a clear winner, and one scenario where they are both good, but one is better than the other. Simulated pairwise evaluation We recruited 24 crowd workers for our human evaluation. Figure 5 shows the interface used for human evaluation. We consider both the ‘Tie’ and ‘Both are bad’ options to be Ties. B CRITERIA-WISE EVALUATION The criteria-wise win rate (%) across all the methods are shown in Figure 6. The criteria-wise win rate was calculated by getting the average win-rate of the preference combinations that contained the specific preference dimension. For example, when calculating the criteria-wise win rate of ‘Elementary’, we got the average win-rate of the preference combinations that contained the ‘Elementary’ preference, which includes AAA, AAB, ABA, and ABB. C THE FULL LIST OF EVALUATION PROMPTS The full list of evaluation prompts used in our experiments are provided in Table 5 D DETAILED RESULTS FOR HUMAN EVALUATION AND GPT-4 EVALUATION We provide detailed results (win / loss / tie for each of the preference combinations for our main experimental results. Table 6 shows the GPT4 evaluation and Table 7 shows the human evaluation results. E EXAMPLES OF P-SOUPS TEXT GENERATIONS Table 8 shows empirical examples of the text generated from each preference combination of the 16 preference combination experiments for the same prompt.

Personalized Soups: LLM Alignment Via Parameter Merging - Conclusion & References

This paper is available on arxiv under CC 4.0 license. . Authors: Gemini Team, Google Table of Links Abstract and Introduction Model Architecture Training Infrastructure Training Dataset Evaluation Responsible Deployment Discussion and Conclusion, References Contributions and Acknowledgments Appendix 8. Contributions and Acknowledgments Leads Rohan Anil, Co-Lead, Text Sebastian Borgeaud, Co-Lead, Text Yonghui Wu, Co-Lead, Text Jean-Baptiste Alayrac, Co-Lead, MM Vision Jiahui Yu, Co-Lead, MM Vision Radu Soricut*, Co-Lead, MM Vision* Johan Schalkwyk, Lead, MM Audio Andrew M. Dai, Co-Lead, Data Anja Hauth*, Co-Lead, Data* Katie Millican, Co-Lead, Data David Silver, Co-Lead, Fine-Tuning Slav Petrov, Co-Lead, Fine-Tuning Melvin Johnson, Lead, Instruction Tuning Ioannis Antonoglou*, Co-Lead, RL Techniques* Julian Schrittwieser, Co-Lead, RL Techniques Amelia Glaese, Lead, Human Data Jilin Chen, Lead, Safety Emily Pitler, Co-Lead, Tool Use Timothy Lillicrap, Co-Lead, Tool Use Angeliki Lazaridou, Co-Lead, Eval Orhan Firat, Co-Lead, Eval James Molloy, Co-Lead, Infra Michael Isard, Co-Lead, Infra Paul R. Barham, Co-Lead, Infra Tom Hennigan, Co-Lead, Infra Benjamin Lee, Co-Lead, Codebase & Parallelism Fabio Viola, Co-Lead, Codebase & Parallelism Malcolm Reynolds, Co-Lead, Codebase & Parallelism Yuanzhong Xu, Co-Lead, Codebase & Parallelism Ryan Doherty, Lead, Ecosystem Eli Collins, Lead, Product Clemens Meyer, Co-Lead, Operations Eliza Rutherford, Co-Lead, Operations Erica Moreira, Co-Lead, Operations Kareem Ayoub, Co-Lead, Operations Megha Goel, Co-Lead, Operations Core Contributors George Tucker Enrique Piqueras Maxim Krikun Iain Barr Nikolay Savinov Ivo Danihelka Becca Roelofs Core Contributors Anaïs White Anders Andreassen Tamara von Glehn Lakshman Yagati Mehran Kazemi Lucas Gonzalez Misha Khalman Jakub Sygnowski Alexandre Frechette Charlotte Smith Laura Culp Lev Proleev Yi Luan Xi Chen James Lottes Nathan Schucher Federico Lebron Alban Rrustemi Natalie Clay Phil Crone Tomas Kocisky Jeffrey Zhao Bartek Perz Dian Yu Heidi Howard Adam Bloniarz Jack W. Rae Han Lu Laurent Sifre Marcello Maggioni Fred Alcober Dan Garrette Megan Barnes Shantanu Thakoor Jacob Austin Gabriel Barth-Maron William Wong Rishabh Joshi Rahma Chaabouni Deeni Fatiha Arun Ahuja Ruibo Liu Yunxuan Li Sarah Cogan Jeremy Chen Core Contributors Chao Jia Chenjie Gu Qiao Zhang Jordan Grimstad Ale Jakse Hartman Martin Chadwick Gaurav Singh Tomar Xavier Garcia Evan Senter Emanuel Taropa Thanumalayan Sankaranarayana Pillai Jacob Devlin Michael Laskin Diego de Las Casas Dasha Valter Connie Tao Lorenzo Blanco Adrià Puigdomènech Badia David Reitter Mianna Chen Jenny Brennan Clara Rivera Sergey Brin Shariq Iqbal Gabriela Surita Jane Labanowski Abhi Rao Stephanie Winkler Emilio Parisotto Yiming Gu Kate Olszewska Yujing Zhang Ravi Addanki Antoine Miech Annie Louis Laurent El Shafey Denis Teplyashin Geoff Brown Elliot Catt Nithya Attaluri Jan Balaguer Jackie Xiang Pidong Wang Zoe Ashwood Anton Briukhov Albert Webson Sanjay Ganapathy Smit Sanghavi Core Contributors Ajay Kannan Ming-Wei Chang Axel Stjerngren Josip Djolonga Yuting Sun Ankur Bapna Matthew Aitchison Pedram Pejman Henryk Michalewski Tianhe Yu Cindy Wang Juliette Love Junwhan Ahn Dawn Bloxwich Kehang Han Peter Humphreys Thibault Sellam James Bradbury Varun Godbole Sina Samangooei Bogdan Damoc Alex Kaskasoli Sébastien M. R. Arnold Vijay Vasudevan Shubham Agrawal Jason Riesa Dmitry Lepikhin Richard Tanburn Srivatsan Srinivasan Hyeontaek Lim Sarah Hodkinson Pranav Shyam Johan Ferret Steven Hand Ankush Garg Tom Le Paine Jian Li Yujia Li Minh Giang Alexander Neitz Zaheer Abbas Sarah York Machel Reid Elizabeth Cole Aakanksha Chowdhery Dipanjan Das Dominika Rogozińska Vitaly Nikolaev Core Contributors Pablo Sprechmann Zachary Nado Lukas Zilka Flavien Prost Luheng He Marianne Monteiro Gaurav Mishra Chris Welty Josh Newlan Dawei Jia Miltiadis Allamanis Clara Huiyi Hu Raoul de Liedekerke Justin Gilmer Carl Saroufim Shruti Rijhwani Shaobo Hou Disha Shrivastava Anirudh Baddepudi Alex Goldin Adnan Ozturel Albin Cassirer Yunhan Xu Daniel Sohn Devendra Sachan Reinald Kim Amplayo Craig Swanson Dessie Petrova Shashi Narayan Arthur Guez Siddhartha Brahma Jessica Landon Miteyan Patel Ruizhe Zhao Kevin Villela Luyu Wang Wenhao Jia Matthew Rahtz Mai Giménez Legg Yeung Hanzhao Lin James Keeling Petko Georgiev Diana Mincu Boxi Wu Salem Haykal Rachel Saputro Kiran Vodrahalli Core Contributors James Qin Zeynep Cankara Abhanshu Sharma Nick Fernando Will Hawkins Behnam Neyshabur Solomon Kim Adrian Hutter Priyanka Agrawal Alex Castro-Ros George van den Driessche Tao Wang Fan Yang Shuo-yiin Chang Paul Komarek Ross McIlroy Mario Lučić Guodong Zhang Wael Farhan Michael Sharman Paul Natsev Paul Michel Yong Cheng Yamini Bansal Siyuan Qiao Kris Cao Siamak Shakeri Christina Butterfield Justin Chung Paul Kishan Rubenstein Shivani Agrawal Arthur Mensch Kedar Soparkar Karel Lenc Timothy Chung Aedan Pope Loren Maggiore Jackie Kay Priya Jhakra Shibo Wang Joshua Maynez Mary Phuong Taylor Tobin Andrea Tacchetti Maja Trebacz Kevin Robinson Yash Katariya Sebastian Riedel Core Contributors Paige Bailey Kefan Xiao Nimesh Ghelani Lora Aroyo Ambrose Slone Neil Houlsby Xuehan Xiong Zhen Yang Elena Gribovskaya Jonas Adler Mateo Wirth Lisa Lee Music Li Thais Kagohara Jay Pavagadhi Sophie Bridgers Anna Bortsova Sanjay Ghemawat Zafarali Ahmed Tianqi Liu Richard Powell Vijay Bolina Mariko Iinuma Polina Zablotskaia James Besley Da-Woon Chung Timothy Dozat Ramona Comanescu Xiance Si Jeremy Greer Guolong Su Martin Polacek Raphaël Lopez Kaufman Simon Tokumine Hexiang Hu Elena Buchatskaya Yingjie Miao Mohamed Elhawaty Aditya Siddhant Nenad Tomasev Jinwei Xing Christina Greer Helen Miller Shereen Ashraf Aurko Roy Zizhao Zhang Ada Ma Angelos Filos Core Contributors Milos Besta Rory Blevins Ted Klimenko Chih-Kuan Yeh Soravit Changpinyo Jiaqi Mu Oscar Chang Mantas Pajarskas Carrie Muir Vered Cohen Charline Le Lan Krishna Haridasan Amit Marathe Steven Hansen Sholto Douglas Rajkumar Samuel Mingqiu Wang Sophia Austin Chang Lan Jiepu Jiang Justin Chiu Jaime Alonso Lorenzo Lars Lowe Sjösund Sébastien Cevey Zach Gleicher Thi Avrahami Anudhyan Boral Hansa Srinivasan Vittorio Selo Rhys May Konstantinos Aisopos Léonard Hussenot Livio Baldini Soares Kate Baumli Michael B. Chang Adrià Recasens Ben Caine Alexander Pritzel Filip Pavetic Fabio Pardo Anita Gergely Justin Frye Vinay Ramasesh Dan Horgan Kartikeya Badola Nora Kassner Subhrajit Roy Ethan Dyer Core Contributors Víctor Campos Alex Tomala Yunhao Tang Dalia El Badawy Elspeth White Basil Mustafa Oran Lang Abhishek Jindal Sharad Vikram Zhitao Gong Sergi Caelles Ross Hemsley Gregory Thornton Fangxiaoyu Feng Wojciech Stokowiec Ce Zheng Phoebe Thacker Çağlar Ünlü Zhishuai Zhang Mohammad Saleh James Svensson Max Bileschi Piyush Patil Ankesh Anand Roman Ring Katerina Tsihlas Arpi Vezer Marco Selvi Toby Shevlane Mikel Rodriguez Tom Kwiatkowski Samira Daruki Keran Rong Allan Dafoe Nicholas FitzGerald Keren Gu-Lemberg Mina Khan Lisa Anne Hendricks Marie Pellat Vladimir Feinberg James Cobon-Kerr Tara Sainath Maribeth Rauh Sayed Hadi Hashemi Richard Ives Yana Hasson YaGuang Li Eric Noland Core Contributors Yuan Cao Nathan Byrd Le Hou Qingze Wang Thibault Sottiaux Michela Paganini Jean-Baptiste Lespiau Alexandre Moufarek Samer Hassan Kaushik Shivakumar Joost van Amersfoort Amol Mandhane Pratik Joshi Anirudh Goyal Matthew Tung Andrew Brock Hannah Sheahan Vedant Misra Cheng Li Nemanja Rakićević Mostafa Dehghani Fangyu Liu Sid Mittal Junhyuk Oh Seb Noury Eren Sezener Fantine Huot Matthew Lamm Nicola De Cao Charlie Chen Contributors Gamaleldin Elsayed Ed Chi Mahdis Mahdieh Ian Tenney Nan Hua Ivan Petrychenko Patrick Kane Dylan Scandinaro Rishub Jain Jonathan Uesato Romina Datta Adam Sadovsky Oskar Bunyan Dominik Rabiej Shimu Wu John Zhang Contributors Gautam Vasudevan Edouard Leurent Mahmoud Alnahlawi Ionut Georgescu Nan Wei Ivy Zheng Betty Chan Pam G Rabinovitch Piotr Stanczyk Ye Zhang David Steiner Subhajit Naskar Michael Azzam Matthew Johnson Adam Paszke Chung-Cheng Chiu Jaume Sanchez Elias Afroz Mohiuddin Faizan Muhammad Jin Miao Andrew Lee Nino Vieillard Sahitya Potluri Jane Park Elnaz Davoodi Jiageng Zhang Jeff Stanway Drew Garmon Abhijit Karmarkar Zhe Dong Jong Lee Aviral Kumar Luowei Zhou Jonathan Evens William Isaac Zhe Chen Johnson Jia Anselm Levskaya Zhenkai Zhu Chris Gorgolewski Peter Grabowski Yu Mao Alberto Magni Kaisheng Yao Javier Snaider Norman Casagrande Paul Suganthan Evan Palmer Contributors Geoffrey Irving Edward Loper Manaal Faruqui Isha Arkatkar Nanxin Chen Izhak Shafran Michael Fink Alfonso Castaño Irene Giannoumis Wooyeol Kim Mikołaj Rybiński Ashwin Sreevatsa Jennifer Prendki David Soergel Adrian Goedeckemeyer Willi Gierke Mohsen Jafari Meenu Gaba Jeremy Wiesner Diana Gage Wright Yawen Wei Harsha Vashisht Yana Kulizhskaya Jay Hoover Maigo Le Lu Li Chimezie Iwuanyanwu Lu Liu Kevin Ramirez Andrey Khorlin Albert Cui Tian LIN Marin Georgiev Marcus Wu Ricardo Aguilar Keith Pallo Abhishek Chakladar Alena Repina Xihui Wu Tom van der Weide Priya Ponnapalli Caroline Kaplan Jiri Simsa Shuangfeng Li Olivier Dousse Fan Yang Jeff Piper Nathan Ie Contributors Minnie Lui Rama Pasumarthi Nathan Lintz Anitha Vijayakumar Lam Nguyen Thiet Daniel Andor Pedro Valenzuela Cosmin Paduraru Daiyi Peng Katherine Lee Shuyuan Zhang Somer Greene Duc Dung Nguyen Paula Kurylowicz Sarmishta Velury Sebastian Krause Cassidy Hardin Lucas Dixon Lili Janzer Kiam Choo Ziqiang Feng Biao Zhang Achintya Singhal Tejasi Latkar Mingyang Zhang Quoc Le Elena Allica Abellan Dayou Du Dan McKinnon Natasha Antropova Tolga Bolukbasi Orgad Keller David Reid Daniel Finchelstein Maria Abi Raad Remi Crocker Peter Hawkins Robert Dadashi Colin Gaffney Sid Lall Ken Franko Egor Filonov Anna Bulanova Rémi Leblond Vikas Yadav Shirley Chung Harry Askham Luis C. Cobo Contributors Kelvin Xu Felix Fischer Jun Xu Christina Sorokin Chris Alberti Chu-Cheng Lin Colin Evans Hao Zhou Alek Dimitriev Hannah Forbes Dylan Banarse Zora Tung Jeremiah Liu Mark Omernick Colton Bishop Chintu Kumar Rachel Sterneck Ryan Foley Rohan Jain Swaroop Mishra Jiawei Xia Taylor Bos Geoffrey Cideron Ehsan Amid Francesco Piccinno Xingyu Wang Praseem Banzal Petru Gurita Hila Noga Premal Shah Daniel J. Mankowitz Alex Polozov Nate Kushman Victoria Krakovna Sasha Brown MohammadHossein Bateni Dennis Duan Vlad Firoiu Meghana Thotakuri Tom Natan Anhad Mohananey Matthieu Geist Sidharth Mudgal Sertan Girgin Hui Li Jiayu Ye Ofir Roval Reiko Tojo Contributors Michael Kwong James Lee-Thorp Christopher Yew Quan Yuan Sumit Bagri Danila Sinopalnikov Sabela Ramos John Mellor Abhishek Sharma Aliaksei Severyn Jonathan Lai Kathy Wu Heng-Tze Cheng David Miller Nicolas Sonnerat Denis Vnukov Rory Greig Jennifer Beattie Emily Caveness Libin Bai Julian Eisenschlos Alex Korchemniy Tomy Tsai Mimi Jasarevic Weize Kong Phuong Dao Zeyu Zheng Frederick Liu Fan Yang Rui Zhu Mark Geller Tian Huey Teh Jason Sanmiya Evgeny Gladchenko Nejc Trdin Andrei Sozanschi Daniel Toyama Evan Rosen Sasan Tavakkol Linting Xue Chen Elkind Oliver Woodman John Carpenter George Papamakarios Rupert Kemp Sushant Kafle Tanya Grunina Rishika Sinha Contributors Alice Talbert Abhimanyu Goyal Diane Wu Denese Owusu-Afriyie Cosmo Du Chloe Thornton Jordi Pont-Tuset Pradyumna Narayana Jing Li Saaber Fatehi John Wieting Omar Ajmeri Benigno Uria Tao Zhu Yeongil Ko Laura Knight Amélie Héliou Ning Niu Shane Gu Chenxi Pang Dustin Tran Yeqing Li Nir Levine Ariel Stolovich Norbert Kalb Rebeca Santamaria-Fernandez Sonam Goenka Wenny Yustalim Robin Strudel Ali Elqursh Balaji Lakshminarayanan Charlie Deck Shyam Upadhyay Hyo Lee Mike Dusenberry Zonglin Li Xuezhi Wang Kyle Levin Raphael Hoffmann Dan Holtmann-Rice Olivier Bachem Summer Yue Sho Arora Eric Malmi Daniil Mirylenka Qijun Tan Christy Koh Soheil Hassas Yeganeh Contributors Siim Põder Steven Zheng Francesco Pongetti Mukarram Tariq Yanhua Sun Lucian Ionita Mojtaba Seyedhosseini Pouya Tafti Ragha Kotikalapudi Zhiyu Liu Anmol Gulati Jasmine Liu Xinyu Ye Bart Chrzaszcz Lily Wang Nikhil Sethi Tianrun Li Ben Brown Shreya Singh Wei Fan Aaron Parisi Joe Stanton Chenkai Kuang Vinod Koverkathu Christopher A. Choquette-Choo Yunjie Li TJ Lu Abe Ittycheriah Prakash Shroff Pei Sun Mani Varadarajan Sanaz Bahargam Rob Willoughby David Gaddy Ishita Dasgupta Guillaume Desjardins Marco Cornero Brona Robenek Bhavishya Mittal Ben Albrecht Ashish Shenoy Fedor Moiseev Henrik Jacobsson Alireza Ghaffarkhah Morgane Rivière Alanna Walton Clément Crepy Alicia Parrish Contributors Yuan Liu Zongwei Zhou Clement Farabet Carey Radebaugh Praveen Srinivasan Claudia van der Salm Andreas Fidjeland Salvatore Scellato Eri Latorre-Chimoto Hanna Klimczak-Plucińska David Bridson Dario de Cesare Tom Hudson Piermaria Mendolicchio Lexi Walker Alex Morris Ivo Penchev Matthew Mauger Alexey Guseynov Alison Reid Seth Odoom Lucia Loher Victor Cotruta Madhavi Yenugula Dominik Grewe Anastasia Petrushkina Tom Duerig Antonio Sanchez Steve Yadlowsky Amy Shen Amir Globerson Adam Kurzrok Lynette Webb Sahil Dua Dong Li Preethi Lahoti Surya Bhupatiraju Dan Hurt Haroon Qureshi Ananth Agarwal Tomer Shani Matan Eyal Anuj Khare Shreyas Rammohan Belle Lei Wang Chetan Tekur Mihir Sanjay Kale Jinliang Wei Contributors Ruoxin Sang Brennan Saeta Tyler Liechty Yi Sun Yao Zhao Stephan Lee Pandu Nayak Doug Fritz Manish Reddy Vuyyuru John Aslanides Nidhi Vyas Martin Wicke Xiao Ma Taylan Bilal Evgenii Eltyshev Daniel Balle Nina Martin Hardie Cate James Manyika Keyvan Amiri Yelin Kim Xi Xiong Kai Kang Florian Luisier Nilesh Tripuraneni David Madras Mandy Guo Austin Waters Oliver Wang Joshua Ainslie Jason Baldridge Han Zhang Garima Pruthi Jakob Bauer Feng Yang Riham Mansour Jason Gelman Yang Xu George Polovets Ji Liu Honglong Cai Warren Chen XiangHai Sheng Emily Xue Sherjil Ozair Adams Yu Christof Angermueller Contributors Xiaowei Li Weiren Wang Julia Wiesinger Emmanouil Koukoumidis Yuan Tian Anand Iyer Madhu Gurumurthy Mark Goldenson Parashar Shah MK Blake Hongkun Yu Anthony Urbanowicz Jennimaria Palomaki Chrisantha Fernando Kevin Brooks Ken Durden Harsh Mehta Nikola Momchev Elahe Rahimtoroghi Maria Georgaki Amit Raul Sebastian Ruder Morgan Redshaw Jinhyuk Lee Komal Jalan Dinghua Li Ginger Perng Blake Hechtman Parker Schuh Milad Nasr Mia Chen Kieran Milan Vladimir Mikulik Trevor Strohman Juliana Franco Tim Green Program Leads Demis Hassabis Koray Kavukcuoglu Overall Technical Leads (equal contribution) Jeffrey Dean Oriol Vinyals The roles are defined as below: • : Individual(s) responsible for the sub-team throughout the project. Lead Individual that had significant impact throughout the project. • Core Contributor: : Individual that had contributions to the project and was partially involved with the effort. • Contributor Responsible for the organizational aspects of the Gemini effort • Program Lead: Responsible for the technical direction of the overall Gemini effort • Overall Technical Lead: Within each role, contributions are equal, and are listed in a randomized order. Ordering within each role does not indicate ordering of the contributions. Gemini is a cross-Google effort, with members from Google DeepMind (GDM), Google Research (GR), Knowledge and Information (K&I), Core ML, Cloud, Labs, and more. We thank our reviewers and colleagues for their valuable discussions and feedback on the report— Alexandra Belias, Arielle Bier, Eleanor Tomlinson, Emily Hossellman, Gaby Pearl, Helen King, Hollie Dobson, Jaclyn Konzelmann, Jennifer Beroshi, Joel Moss, Jon Small, Jonathan Fildes, Oli Gaymond, Rebecca Bland, Reena Jana, and Tom Lue. Our work is made possible by the dedication and efforts of numerous teams at Google. We would like to acknowledge the support from Abhi Mohan, Adekunle Bello, Aishwarya Nagarajan, Alaa Saade, Alejandro Lince, Alexander Chen, Alexander Kolbasov, Alexander Schiffhauer, Amar Subramanya, Ameya Shringi, Amin Vahdat, Anda Rabatić, Anthonie Gross, Antoine Yang, Anthony Green, Anton Ruddock, Art Khurshudov, Artemis Chen, Arthur Argenson, Avinatan Hassidim, Beiye Liu, Benjamin Schroeder, Bin Ni, Brett Daw, Bryan Chiang, Burak Gokturk, Carl Crous, Carrie Grimes Bostock, Charbel Kaed, Charlotte Banks, Che Diaz, Chris Larkin, Christy Lian, Claire Cui, Clare Bycroft, Corentin Tallec, Daniel Herndon, Dave Burke, David Battle, David Engel, Dipannita Shaw, Donghyun Koo, Doug Ritchie, Dragos Stefanescu, Elissa Wolf, Emre Sargin, Eran Ofek, Eric Herren, Estella King, Fatema Alkhanaizi, Felix Gimeno, Fernando Pereira, Florent Altché, Gabriel Carvajal, Gaurav Gandhi, George Powell, Goran Pavičić, Harry Richardson, Hassan Wassel, Hongji Li, Idan Szpektor, Igor Ivanisevic, Ivan Jambrešić, Ivan Jurin, Jade Fowler, James Assiene, Jay Yagnik, Jeanbastien Grill, Jeff Seibert, Jenna LaPlante, Jessica Austin, Jianxing Lu, Jim O’Keeffe, Jin Huang, Joe Heyward, Johannes Welbl, John Jumper, Jonathan Caton, Josh Woodward, Joshua Foster, Kathryn Tunyasuvunakool, Katrina Wong, Kavya Kopparapu, Kelvin Nguyen, Kira Yin, Konstantin Sharlaimov, Kun Li, Lee Hong, Lilly Taylor, Longfei Shen, Luc Mercier, Maciej Mikuła, Mania Abdi, Manuel Sanchez, Maria Ines Aranguren, Mario Carlos Cortes III, Matthew Tait, Matthias Lochbrunner, Mehdi Ghissassi, Micah Mosley, Michael Bendersky, Michael Figurnov, Michael Harris, Michael Mathieu, Michael O’Neill, Michael Vorburger, Mihir Paradkar, Nandita Dukkipati, Nathan Carter, Nathan Watson, Neil Rabinowitz, Nikhil Dandekar, Nishant Ranka, Obaid Sarvana, Olcan Sercinoglu, Olivier Lacombe, Ottavia Bertolli, Paul Caron, Pranesh Srinivasan, Praveen Kumar, Rahul Sukthankar, Raia Hadsell, Rajagopal Ananthanarayanan, Roberto Lupi, Rosie Zou, Sachin Menezes, Sadegh Jazayeri, Sam Cheung, Sameer Bidichandani, Sania Alex, Sanjiv Kumar, Sara Wiltberger, Sarah Fitzgerald, Saz Basu, Sebastian Nowozin, Shannon Hepburn, Shayne Cardwell, Sissie Hsiao, Srinivasan Venkatachary, Sugato Basu, Sundar Pichai, Sundeep Tirumalareddy, Susannah Young, Swetha Vijayaraghavan, Tania Bedrax-Weiss, Taylor Applebaum, Teiva Harsanyi, Terry Chen, Tim Blyth, Ting Liu, Tom Cobley, Tomas Izo, Trystan Upstill, Varun Singhai, Vedrana Klarić Trupčević, Victor Cai, Vladimir Pudovkin, Vu Dang, Wenbo Zhao, Wesley Crow, Wesley Szeng, Xiaodan Song, Yazhou Zu, Ye Tian, Yicong Wang, Yixing Wang, Yossi Matias, Yunlong Jiao, Zachary Jessup, Zhenchuan Pang, Žiga Avsec, Zimeng Yang, and Zoubin Ghahramani. We’d also like to recognize the AlphaCode team, the Borg Scheduling team, the Facilities team, the Gemini Demo Team, the Global Server Ops (GSO) team, the JAX team, the the Legal team, ML SRE team, the ML Supercomputer (MLSC) team, the PartIR team, the Platforms Infrastructure Engineering (PIE) team, and the XLA Compiler team. We thank everyone at Google not explicitly mentioned above, who have shared excitement, given feedback on early Gemini models or created interesting demo uses of Gemini, and worked with or supported the core Gemini team on many aspects of this project.

Gemini -  A Family of Highly Capable Multimodal Models: Contributions and Acknowledgments

WOW Summit Dubai 2023, the World of WEB3 Summit, recently concluded with resounding success at the opulent Atlantis the Royal in Dubai. This event showcased an extraordinary lineup of speakers and esteemed sponsors, leaving an indelible mark on the world of blockchain and Web3 technology. , Global CEO of WOW Summit, expressed his enthusiasm, stating, Ivan Ivanov "WOW Summit Dubai 2023 has exceeded our wildest expectations. It was a landmark gathering that brought together Web3 enthusiasts, industry leaders, and government officials to shape the future of blockchain technology." The event featured some amazing panel discussions and keynotes that illuminated the path forward for blockchain and Web3 technology. The Summit featured an array of captivating panel discussions and keynote presentations. Among the standout topics were, Exploring the Fusion of AI, Metaverse, Gaming, Fashion, and NFTs, Global Strategies for Amplifying Revenue: Unlocking the Potential of Corporate Blockchain Providers, Early-Stage Funding Opportunities in Web3 Projects and Acceleration, Current State of Decentralized Media, Advancements in Web3 Protocols: Pioneering the Path to Innovation and Progress and several others. The event's sponsors, Farcana, Unicoin, Fastex, demonstrated their unwavering commitment to fostering innovation in the blockchain industry. Their visionary leadership and strategic expertise set the stage for transformative discussions on the potential of blockchain. Our sponsors were represented at the event as speakers and boosters in the exhibition hall. This exemplified their commitment to advancing the blockchain industry. Among the sponsors of the event we note such companies as: Darwinbit, ChainUp, Sastana, Beezfi (BizTrip), P2PBet,  Hacken, ICP, EXOLO. Unicoin, a next-generation cryptocurrency, stands out from its predecessors by embracing transparency, SEC compliance, and being backed by a diversified asset portfolio, including real estate and equity in high-growth companies. In contrast, Farcana, a Dubai-based AAA game development studio, is in the process of creating a game bearing the same name. Farcana's unique 4v4, ability-based arena shooter redefines the gaming experience with its innovative 4-role system, strategic gameplay, and full integration of Web3 technology, all while maintaining the high-quality standards associated with AAA gaming. Fastex is a complete Web3-driven ecosystem that introduces diverse centralized and decentralised products and solutions, including Fasttoken (FTN), Fastex Exchange, Fastexverse, Fastex Pay, and ftNFT Marketplace. Driven by constant changes in the world of technologies, the Fastex ecosystem always thinks one step ahead and aims to bring businesses and communities closer to Web3 technologies, making them more accessible than ever. Joining as speakers were also a group of outstanding individuals contributing significantly to the payments industry on Blockchain instead, including (Darwinbit), (Trust Wallet), (Hacken), (P2P Labs), and (Kinetex Network). Their support underscored the collaborative spirit of WOW Summit Dubai 2023. Jeff Zhao Eowyn Chen Igor Bershadskiy Marat Salimov Tigran Bolshoi The event featured distinguished speakers, including (Animoca Brands), (Dubai Blockchain Centre), (Director at EMARATSEC, Co-chair at the WEF global future council, Director for Center at Cyber Security New York University AD), (MENA Fintech Association), (Circle), (Chainanalysis), (Crypto Valley Partners), (UNICOIN), (Farcana), (Oracle), and other luminaries who shared profound insights and valuable discussions. Yat Siu Dr. Marwan Alzarouni Dr. Hoda Alkhzaimi Nameer Khan Miriam Kiwan Mohamed Issa Sam Katiela Julian Sperring-Toy Islam Shazhaev Joy John Prominent figures such as , , , , also graced the event, adding to its prestige. Michael Terpin Gurvinder Ahluwalia Christian Gleich Nick Spanos Mansoor Madhavji The Summit was honored by the presence of distinguished guests and esteemed media personalities, including , the esteemed from Moongames, as well as the notable presence of and (GuyWay events). Sheikh Ali Rashed Ali Saeed Al Maktoum Carl Runefelt Davinci Jeremie Guy Yanpolskiy The results of the WOW Summit Dubai Startup competition serves as a glittering showcase, highlighting the brilliant innovations and rising stars within the dynamic realms of blockchain and Web3 technology. From a pool of over a hundred spirited startup contenders, the selection of the top 10 was an inclusive and decentralized process, driven by the vibrant community using Cyrator (available at cyrator.com). This online platform became the epicenter of independent decentralized reviews, inquiries, and profound insights, all thoughtfully validated, and endorsed by esteemed experts. These well-considered deliberations are closely scrutinized by a committee of discerning investors. They're thrilled to introduce the distinguished winner of their Startup competition, hailing all the way from France, the brilliant minds behind the tokenized investment fund named Petale. This remarkable achievement has garnered the attention of MMPro Trust and its esteemed investors, who are now contemplating an investment of up to $1 million in the Petale project. Additionally, the project is set to embark on a series of meetings with tier-1 investment funds in Dubai. In an added boost of support, the Petale project has secured three months of invaluable market-making assistance, comprehensive listing maintenance, and expert trade strategy management courtesy of Market Making Pro, all as a well-deserved reward for emerging triumphant in the WOW Summit Startup Competition. This accomplishment underlines WOW Summit's steadfast dedication not only to recognizing exceptional talent but also to providing a vital launchpad for entrepreneurial aspirations. Furthermore, their victorious startups have not only earned the prestigious accolade but have also been generously rewarded with a slew of prizes from industry leaders such as AWS and various other esteemed partners. The WOW GROWTH program has also extended its nurturing hand to the top 10 finalists, offering a three-month acceleration program complete with comprehensive business development support and guidance on investor relations. This support will span across regions of interest, including Asia (HK Hub), the MENA region (UAE Hub), and Europe (Swiss Hub). In a groundbreaking collaboration with the Internet Computer Protocol (ICP), WOW Summit and GROWTH have launched an exciting Ideathon program, designed to cater to companies in their early stages, enabling them to test their innovative concepts and find the perfect tech team to bring these ideas to life. The Ideathon is now open for participation throughout the months of October and November 2023, while the forthcoming hackathon is scheduled to take place during the WOW Summit in Hong Kong 2024. The exclusive media zone, featuring moderators from Ana Solana (JETA agency) and Adel Bhurtun from Web3TV, provided a platform for in-depth coverage and analysis of the event's key moments. WOW Summit Dubai 2023's art zone showcased an impressive array of digital and NFT artists. Amrita Sethi, the event's headliner, crafted five unique works and is recognized as the UAE's first NFT artist, as well as a top-tier Physical and Digital Artist. For the WOW Summit, Amrita Sethi unveiled her latest masterpiece series titled "Art and Tech" aiBYTEs, representing a captivating evolution of her distinctive style. In a remarkable fusion of art and technology, she collaborated with ChatGPT to craft a poetic narrative that envisions how the transition from Web2 to Web3 will inspire our world. Subsequently, she harnessed the creative power of Midjourney to transform this narrative into stunning visual imagery. Vesa, a renowned digital art pioneer for over 15 years, is considered one of the initial artists to delve into crypto art and NFTs. His notable awards include NFT Artist of the Year (AIBC Summit, 2023) and top Web3 Artists accolades from L’Officiel Arabia. Naama Pozniak, the CEO of Paz Holding, Inc., and LetzGetPhygital, stood out as a Web3 Educator, NFT Artist, and multifaceted professional known for her contributions to the art world. WOW Summit Dubai 2023 lived up to its promise as an unmissable Web3 event that will undoubtedly shape the future of blockchain technology. Attendees were treated to a unique experience filled with knowledge sharing, networking opportunities, and exploration of cutting-edge developments in the Web3 ecosystem. WOW Summit is now gearing up for their Hong Kong edition in 2024, scheduled for March 26-27. Secure your super now. early bird tickets About WOW Summit: WOW Summit is a leading global Web3 event that unites distinguished industry titans, esteemed government officials, visionary funds, venture capitalists, NFT and digital artists, entrepreneurs, and multinational corporations. The Summit drives the innovative trajectory of Web3, covering cutting-edge trends and innovations in technology. It explores themes including the Web2 - Web3 transition, CBDCs, regulatory landscapes, asset tokenization, and the societal impact of blockchain and DLT technologies. Hosted by GuyWay, powered by MarketMakingPro, and co-organized by Uvecon.vc and Quantum Leap Strategy, WOW Summit has a history of hosting distinguished speakers.

WOW Summit Dubai 2023: A Massive Success Shaping the Future of Blockchain Technology

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