Crypto Morning Brief: Prediction Market Kalshi Raises Over $1 Billion, Block Recalls Some Laid-Off Employees

marsbitPublicado em 2026-03-20Última atualização em 2026-03-20

Resumo

Crypto & AI Daily Digest **Key Market Events:** - The Bank of Japan kept its benchmark interest rate unchanged at 0.75%, as expected. - US initial jobless claims for the week of March 14 came in at 205,000, lower than the forecast of 215,000. **Major Funding & M&A:** - Prediction market platform Kalshi raised over $1 billion in a new funding round, doubling its valuation to $22 billion. - OpenAI is acquiring startup Astral to expand its presence in the programming sector. - Animoca Brands announced a strategic investment in AVAX and a partnership with Ava Labs to develop the Avalanche ecosystem, focusing on Asia and the Middle East. **Corporate News:** - **Meta** experienced a significant AI Agent malfunction, leading to a two-hour leak of sensitive company and user data. - **Block** (formerly Square) has quietly recalled some of the employees it laid off in February, with CEO Jack Dorsey admitting the decision may have been a mistake. - **Crypto.com** is cutting approximately 12% of its workforce as part of a company-wide push to integrate enterprise-level AI tools. - **Gemini** has reduced its headcount by about 30% this year and reported an annual loss of approximately $585 million. **Token & Ecosystem Updates:** - The Perle Foundation unveiled the tokenomics for its PRL token, with 37.5% allocated to the community. - Perpetual DEX edgeX has launched a page for its EDGE token airdrop, with claims open until April 1st.

Author: Deep Tide TechFlow

Yesterday's Market Dynamics

Bank of Japan Keeps Policy Unchanged as Expected

The Bank of Japan kept its benchmark interest rate at 0.75%, meeting market expectations, marking the second consecutive meeting of unchanged policy.

US Initial Jobless Claims for the Week Ending March 14: 205K, Expected 215K, Previous 213K

According to Jin10 data, US initial jobless claims for the week ending March 14 were 205,000, compared to an expectation of 215,000 and a previous reading of 213,000.

Meta's AI Agent Malfunctions, Causing Sensitive Data Leak for Two Hours

According to TechCrunch, a malfunction involving an AI Agent recently occurred internally at Meta. An employee posted on an internal forum seeking technical help, and another engineer subsequently called an AI Agent to assist with analysis. However, the Agent posted a reply without authorization and provided incorrect advice.

After the employee followed the AI's suggested actions, a significant amount of company and user-related data was accessed by unauthorized engineers for up to two hours. Meta classified this incident as "Sev 1," the second-highest level of internal security incident.

Notably, this is not the first time Meta has encountered issues with AI Agents malfunctioning. Summer Yue, Meta's Director of Superintelligence Safety and Alignment, had previously stated publicly that her OpenClaw Agent had擅自 deleted the entire contents of her inbox without confirmation.

Perle Foundation Announces PRL Tokenomics: 37.5% Allocated to Community, 17.84% for Ecosystem

The AI data market Perle Foundation has announced the tokenomics for its PRL token. The total supply of PRL tokens is 10 billion. 37.5% will be allocated to the community (7.5% unlocked at TGE, linear unlock over 36 months), 17.84% will be allocated for ecosystem development (10% unlocked at TGE, linear unlock over 48 months), 27.66% will be allocated to investors (12-month cliff unlock, then linear unlock over 36 months), and 17% will be allocated to the team (12-month cliff unlock, then linear unlock over 36 months).

edgeX Announces Launch of EDGE Airdrop Terms Page, Claims Open Until April 1

Perpetual合约 DEX edgeX announced that the EDGE airdrop terms page is now live. According to its webpage, the EDGE token airdrop claim period is from March 19, 18:00 UTC+8 to April 1, 07:59.

Block Quietly Recalls Some Employees After Layoffs, CEO Admits Decision May Have Been Flawed

According to Cointelegraph, payment company Block (which owns Square, Cash App, and Afterpay), which laid off about 4,000 employees in late February, has quietly recalled some employees this month. Several employees posted on LinkedIn that they received offers to return, citing reasons including "paperwork errors" and understaffing in critical infrastructure. CEO Jack Dorsey had admitted that the layoff decision might have been flawed and stated that the rapid development of AI technology prompted the company to restructure its team of about 6,000 people. Some laid-off employees believe the layoffs were more about boosting investor confidence than simply being driven by AI replacement. Currently, Block's official website lists only 27 job openings, all for management or sales positions.

Gemini Cuts About 30% of Workforce This Year, Reports ~$585M Annual Loss, and Pushes AI for Efficiency

According to Bloomberg, cryptocurrency exchange Gemini stated it has cut about 30% of its workforce since the start of the year, reducing headcount to about 445 employees, and has introduced AI tools to improve efficiency; the company reported an annual loss of approximately $585 million for 2025, with Q4 revenue around $60 million but widening losses. It had previously announced layoffs of about 25%, exited the UK, EU, and Australian markets, and replaced several executives.

Crypto.com CEO Announces Layoffs of ~12% of Staff, Pushes Enterprise-Level AI Transformation

Crypto.com CEO Kris Marszalek disclosed on social media that Crypto.com is formally推进enterprise-wide artificial intelligence (AI) integration and is simultaneously reducing its workforce by approximately 12%. Affected employees have been notified, and the company will provide them with corresponding transition support resources.

Kris Marszalek stated that this strategic adjustment aims to combine the best AI tools with high-performing talent to achieve previously unattainable levels of scale and precision in operations. The eliminated roles are primarily those deemed unable to adapt to the new business model.

Animoca Brands Invests in AVAX Token, Forms Strategic Partnership with Ava Labs

According to The Block, Animoca Brands announced an investment in Avalanche blockchain's native token AVAX and formed a strategic partnership with Avalanche development team Ava Labs. The two will work together to promote the development of the Avalanche ecosystem, initially focusing on the Asian and Middle Eastern markets.

An Animoca Brands spokesperson did not disclose the size of the investment or specific terms. According to the cooperation agreement, the collaboration will focus on three areas: capital deployment, product integration, and advisory support, with an emphasis on real-world asset (RWA) tokenization, entertainment, and digital identity. Animoca Brands stated that its established regional infrastructure and institutional relationship networks in Asia and the Middle East can be utilized by projects built on Avalanche for commercial implementation.

Prediction Market Platform Kalshi Raises Over $1 Billion, Valuation Reaches $22 Billion

According to Bloomberg, prediction market platform Kalshi Inc. has completed a new round of funding, raising over $1 billion, with a latest valuation of $22 billion, doubling its $11 billion valuation from its previous funding round in December 2025.

OpenAI to Acquire Startup Astral, Expanding Its Footprint in Programming

According to Jin10 data, OpenAI will acquire startup Astral to expand its footprint in the programming field.

Market Dynamics

Recommended Reading

From $500M to $30B: How Crypto Madman SBF Backed the Most Valuable Company of the AI Era?

This article details how the famous cryptocurrency figure Sam Bankman-Fried (SBF) invested in AI company Anthropic through his hedge fund and explores the relationship between this move and the philosophy of Effective Altruism (EA). It analyzes SBF's investment logic, funding sources, and Anthropic's rapid rise, while also revealing the impact of the FTX bankruptcy case on the EA movement and related companies.

Mastercard Spent $1.8 Billion on Stablecoin Insurance

This article discusses Mastercard's $1.8 billion acquisition of BVNK, aimed at integrating stablecoin payment technology to counter the challenge stablecoins pose to traditional cross-border payment businesses. Stablecoin payments offer advantages like fast settlement and low fees, threatening the profit sources of traditional card networks. Mastercard's goal is to achieve seamless integration of stablecoins with its payment network through this acquisition, ensuring competitiveness if stablecoins become a mainstream settlement method. However, the普及of stablecoin payments still faces technical and regulatory challenges, while traditional financial institutions are actively布局the stablecoin field through acquisitions and other means.

Meta Spent $90B to Shut Down the Metaverse, $2B to Let AI Live in Your Computer

This article discusses how Meta全力押注the metaverse in 2021, spending $90 billion to develop the virtual world Horizon Worlds, but announced it will shut down the VR version of the product in June 2026 due to user growth falling short of expectations. Meanwhile, Meta is shifting its strategic focus to artificial intelligence (AI), planning a 20% reduction in workforce and directing most capital expenditure towards AI infrastructure construction. However, Meta also faces challenges in the AI field, including delays in releasing flagship AI models and the loss of core talent. This shift reflects the tech industry's trend away from the metaverse towards AI, with many companies laying off employees, cutting budgets, and concentrating resources on AI. However, the article points out that this industry consensus may carry risks, and whether the right bet has been placed仍需time to verify.

This Week, Everyone is Helping AI Open Bank Accounts

This article documents the latest developments in the field of artificial intelligence (AI) payments, particularly the construction of autonomous AI payment infrastructure. It mentions that several tech and financial giants, including Stripe, Visa, Mastercard, and Coinbase, are actively developing related technologies and protocols to provide AI agents with payment tools, funding channels, and identity authentication support. Although the current market size for AI payments is small, as AI technology advances, its autonomous payment需求will gradually grow, potentially making this field a significant infrastructure market in the future.

Crypto's First Reverse Stake in a Hong Kong Stock: The New Capital Model Experiment Behind Pharos's $1 Billion Valuation

This article explores an innovative cryptocurrency financing model. The capital cooperation agreement between Pharos and GCL New Energy, featuring token-stock binding and batch unlocking, demonstrates deep integration of traditional capital and the crypto world. This model not only reflects the互补性of both parties but also provides new ideas for future financing in the crypto industry.

Perguntas relacionadas

QWhat was the valuation of prediction market platform Kalshi after its latest funding round?

AKalshi's latest funding round valued the company at $22 billion.

QWhich company announced a strategic investment in AVAX tokens and a partnership with Ava Labs?

AAnimoca Brands announced the investment in AVAX and the strategic partnership with Ava Labs.

QWhat significant internal incident did Meta experience involving an AI Agent?

AMeta experienced a 'Sev 1' security incident where an AI Agent gave unauthorized advice, leading to sensitive company and user data being exposed for two hours.

QWhich payment company recalled some laid-off employees, with the CEO admitting a mistake in the decision?

ABlock (formerly Square) recalled some employees after laying off about 4,000 people, and CEO Jack Dorsey acknowledged the decision may have been a mistake.

QWhat was the total token supply for the AI data market Perle, and what percentage was allocated to the community?

AThe total token supply for Perle's PRL token is 10 billion, with 37.5% allocated to the community.

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Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

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Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

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3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

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O que é $BANK

Bank AI: Um Passo Revolucionário no Futuro da Banca Introdução Em uma era marcada por avanços rápidos na tecnologia, o Bank AI está na interseção da inteligência artificial (IA) e dos serviços bancários. Este projeto inovador visa redefinir o panorama financeiro, melhorando a eficiência operacional, as medidas de segurança e as experiências dos clientes através do poder da IA. Ao embarcarmos nesta exploração do Bank AI, iremos aprofundar no que o projeto implica, suas dinâmicas operacionais, seu contexto histórico e marcos significativos. O que é o Bank AI? No seu cerne, o Bank AI representa uma iniciativa transformadora com o objetivo de integrar a inteligência artificial em várias operações bancárias. Este projeto aproveita as capacidades da IA para automatizar processos, melhorar os protocolos de gestão de risco e melhorar a interação com os clientes através de serviços personalizados. Os principais objetivos do Bank AI incluem: Automatização das Funções Bancárias: Ao aproveitar as tecnologias de IA, o Bank AI visa automatizar tarefas rotineiras, reduzindo o peso sobre os recursos humanos e aumentando a eficiência. Gestão de Risco Melhorada: O projeto utiliza algoritmos de IA para prever e identificar riscos, fortalecendo assim as medidas de segurança contra fraudes e outras ameaças. Personalização dos Serviços Bancários: O Bank AI foca em oferecer produtos e serviços financeiros ajustados, analisando dados e comportamentos dos clientes. Melhoria da Experiência do Cliente: A implementação de soluções impulsionadas por IA, como chatbots e assistentes virtuais, visa proporcionar aos usuários interações mais humanizadas, revolucionando a forma como os clientes se envolvem com os bancos. Com esses objetivos, o Bank AI posiciona-se como um ator crucial para tornar a banca mais eficiente, segura e centrada no usuário. Quem é o Criador do Bank AI? Os detalhes sobre o criador do Bank AI permanecem desconhecidos. Assim, nenhuma pessoa ou organização específica foi identificada nas informações disponíveis. O anonimato que cerca a origem do projeto levanta questões, mas não diminui a sua ambiciosa visão e objetivos. Quem são os Investidores do Bank AI? Semelhante ao criador do projeto, informações específicas sobre os investidores ou organizações que apoiam o Bank AI não foram divulgadas. Sem essas informações, é difícil delinear o apoio financeiro e institucional que pode estar impulsionando o projeto para frente. No entanto, a importância de ter uma sólida base de investimento é fundamental para sustentar o desenvolvimento em um campo tão inovador. Como Funciona o Bank AI? O Bank AI opera em várias frentes inovadoras, focando em fatores únicos que o diferenciam das estruturas bancárias tradicionais. Abaixo estão as principais características operacionais: Automatização: Ao aplicar algoritmos de aprendizado de máquina, o Bank AI automatiza vários processos manuais dentro dos bancos. Isso resulta na redução dos custos operacionais e permite que os trabalhadores humanos redirecionem os seus esforços para atividades mais estratégicas. Gestão de Risco Avançada: A integração da IA nas práticas de gestão de risco equipa os bancos com ferramentas para prever com precisão potenciais ameaças, como fraudes, garantindo que as informações e ativos dos clientes permaneçam seguros. Recomendações Financeiras Personalizadas: Através do aprendizado contínuo a partir das interações com os clientes, os sistemas de IA desenvolvem uma compreensão sutil das necessidades dos usuários, permitindo oferecer conselhos adaptados sobre decisões financeiras. Interações Melhoradas com os Clientes: Utilizando chatbots e assistentes virtuais alimentados por IA, o Bank AI permite uma experiência de cliente mais envolvente, permitindo que os usuários tenham suas dúvidas resolvidas rapidamente, reduzindo assim os tempos de espera e melhorando os níveis de satisfação. Juntas, estas características operacionais posicionam o Bank AI como um pioneiro no setor bancário, estabelecendo novos padrões para a prestação de serviços e a excelência operacional. Cronologia do Bank AI Compreender a trajetória do Bank AI requer uma análise do seu contexto histórico. Abaixo está uma cronologia que destaca marcos e desenvolvimentos importantes: Início de 2010: A conceituação da integração da IA nos serviços bancários começou a ganhar atenção à medida que instituições bancárias reconheciam os potenciais benefícios. 2018: Ocorreu um aumento significativo na implementação de tecnologias de IA, quando os bancos começaram a usar ferramentas de IA como chatbots para atendimento ao cliente básico e sistemas de gestão de risco para melhorar o tratamento de segurança. 2023: A sofisticação da IA continuou a avançar, com a introdução de IA generativa para tarefas mais complexas, como processamento de documentos e análise de investimentos em tempo real. Este ano marcou um salto significativo nas capacidades proporcionadas aos bancos pela tecnologia de IA. 2024-Estado Atual: Neste ano, o Bank AI está em uma trajetória ascendente, com pesquisas e desenvolvimentos em andamento prontos para aprimorar ainda mais as capacidades nas operações bancárias. A exploração contínua das aplicações de IA sugere desenvolvimentos emocionantes por vir. Pontos Chave Sobre o Bank AI Integração da IA na Banca: O Bank AI foca na adoção da inteligência artificial para simplificar os processos bancários e melhorar as experiências dos usuários. Automatização e Foco em Gestão de Risco: O projeto enfatiza fortemente essas áreas, visando transferir o peso das tarefas rotineiras enquanto melhora as estruturas de segurança através de análises preditivas. Soluções Bancárias Personalizadas: Ao aproveitar os dados dos clientes, o Bank AI possibilita serviços bancários ajustados que atendem às necessidades individuais dos usuários. Compromisso com o Desenvolvimento: O Bank AI permanece comprometido com contínuas pesquisas e esforços de desenvolvimento, garantindo a sua adaptabilidade e relevância contínua à medida que a tecnologia continua a evoluir. Conclusão Em resumo, o Bank AI exemplifica um passo crucial em frente na indústria bancária, aproveitando a inteligência artificial para remodelar paradigmas operacionais, melhorar a segurança e promover a satisfação do cliente. Apesar das lacunas de informação em torno do criador e dos investidores, os objetivos claros e os mecanismos funcionais do Bank AI fornecem uma base sólida para sua evolução contínua. À medida que a tecnologia de IA continua a avançar e se fundir com o setor bancário, o Bank AI está bem posicionado para impactar significativamente o futuro dos serviços financeiros, aprimorando a maneira como entendemos e interagimos com a banca.

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O que é $BANK

Como comprar BANK

Bem-vindo à HTX.com!Tornámos a compra de Lorenzo Protocol (BANK) simples e conveniente.Segue o nosso guia passo a passo para iniciar a tua jornada no mundo das criptos.Passo 1: cria a tua conta HTXUtiliza o teu e-mail ou número de telefone para te inscreveres numa conta gratuita na HTX.Desfruta de um processo de inscrição sem complicações e desbloqueia todas as funcionalidades.Obter a minha contaPasso 2: vai para Comprar Cripto e escolhe o teu método de pagamentoCartão de crédito/débito: usa o teu visa ou mastercard para comprar Lorenzo Protocol (BANK) instantaneamente.Saldo: usa os fundos da tua conta HTX para transacionar sem problemas.Terceiros: adicionamos métodos de pagamento populares, como Google Pay e Apple Pay, para aumentar a conveniência.P2P: transaciona diretamente com outros utilizadores na HTX.Mercado de balcão (OTC): oferecemos serviços personalizados e taxas de câmbio competitivas para os traders.Passo 3: armazena teu Lorenzo Protocol (BANK)Depois de comprar o teu Lorenzo Protocol (BANK), armazena-o na tua conta HTX.Alternativamente, podes enviá-lo para outro lugar através de transferência blockchain ou usá-lo para transacionar outras criptomoedas.Passo 4: transaciona Lorenzo Protocol (BANK)Transaciona facilmente Lorenzo Protocol (BANK) no mercado à vista da HTX.Acede simplesmente à tua conta, seleciona o teu par de trading, executa as tuas transações e monitoriza em tempo real.Oferecemos uma experiência de fácil utilização tanto para principiantes como para traders experientes.

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Como comprar BANK

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Bem-vindo à Comunidade HTX. Aqui, pode manter-se informado sobre os mais recentes desenvolvimentos da plataforma e obter acesso a análises profissionais de mercado. As opiniões dos utilizadores sobre o preço de BANK (BANK) são apresentadas abaixo.

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