The most important AI developments from around the world, summarized by AI so you stay informed in minutes.
Last updated: 27/4/2026, 6:57:40 am (IST)
AI Ascends
AI News Daily Top 5
2026-04-27
AIDays.in
- AI's market influence is overshadowing global concerns, creating economic divides.
- AI tools are impacting various sectors, from finance and real estate to software development.
- Companies like OpenAI are refining their AI models, while user demographics for AI assistants are emerging.
01
AI Boom Drowns Out War Fears to Fuel Asia’s Great Market Divide
This bifurcation highlights a critical shift where technological advancement, specifically AI, is becoming a primary determinant of market performance and economic prosperity across Asia, potentially reshaping investment strategies and regional economic power dynamics.
Bloomberg Tech
02
Our principles
This signals OpenAI's commitment to ethical AGI development, crucial for shaping India's and the world's technological future.
OpenAI Blog
03
To buy this Bay Area home, you’ll need Anthropic equity
This unconventional real estate deal underscores the increasing financial power and perceived future value of prominent AI companies within the investment landscape.
TechCrunch AI
04
Bytes Speak All Languages: Cross-Script Name Retrieval via Contrastive Learning
This advancement has the potential to democratize data access and search functionalities across diverse linguistic and script-based datasets prevalent in India.
Towards Data Science
05
I Reduced My Pandas Runtime by 95% — Here’s What I Was Doing Wrong
This article offers practical, actionable advice for Indian tech professionals working with large datasets, enabling them to significantly improve the efficiency and speed of their data analysis pipelines.
Asian markets are exhibiting a stark divergence, with the AI boom acting as a significant market driver, overshadowing geopolitical anxieties like war fears. This AI-fueled rally is creating a distinct divide, potentially benefiting certain economies and sectors within Asia while others remain stagnant or decline. The narrative suggests that while global instability persists, the transformative potential of AI is creating new investment opportunities and economic growth trajectories specifically within the Asian tech landscape.
Key Takeaways
The AI revolution is a dominant force in Asian market sentiment, superseding geopolitical concerns.
A clear market segmentation is emerging in Asia, driven by AI adoption and related investments.
The economic impact of AI is creating a divergence between growth-oriented and less dynamic markets within the region.
Why it matters: This bifurcation highlights a critical shift where technological advancement, specifically AI, is becoming a primary determinant of market performance and economic prosperity across Asia, potentially reshaping investment strategies and regional economic power dynamics.
OpenAI's latest blog post, authored by Sam Altman, outlines the core principles guiding their pursuit of Artificial General Intelligence (AGI). The company's overarching mission is to develop AGI in a way that benefits all of humanity, emphasizing safety and broad accessibility. These guiding principles aim to ensure the responsible and equitable development and deployment of advanced AI technologies.
Key Takeaways
OpenAI's primary goal is to ensure AGI benefits everyone.
Sam Altman articulates five key principles steering their AGI development.
The focus is on safety and equitable distribution of AGI's advantages.
Why it matters: This signals OpenAI's commitment to ethical AGI development, crucial for shaping India's and the world's technological future.
A unique real estate offering has emerged in Mill Valley, California, where a 13-acre property is being listed with a rather unconventional payment option: Anthropic equity. This suggests a significant level of confidence in the AI company's future valuation, as the seller is willing to accept stakes in the startup as a form of payment for prime Bay Area real estate. The deal highlights the burgeoning intersection of cutting-edge tech and traditional assets, particularly within the AI sector.
Key Takeaways
A 13-acre property in Mill Valley, California, is accepting Anthropic equity as payment.
This unusual deal indicates strong investor or owner confidence in Anthropic's future value.
The transaction showcases a novel way tech equity is being leveraged in high-value asset acquisitions.
Why it matters: This unconventional real estate deal underscores the increasing financial power and perceived future value of prominent AI companies within the investment landscape.
This Towards Data Science article introduces a novel approach for cross-script name retrieval, moving beyond the traditional limitation of learning multiple scripts to a more efficient method of processing names based on their byte representations. By leveraging contrastive learning, the system learns to identify and match names across different writing systems by focusing on underlying phonetic or semantic similarities encoded within their 256-byte representations. This bypasses the need for extensive script-specific training data, making name recognition more scalable and robust.
Key Takeaways
The research proposes using 256-byte representations instead of learning multiple scripts for name retrieval.
Contrastive learning is employed to find similarities in name embeddings across different scripts.
This method aims to significantly reduce the complexity and data requirements for cross-script name recognition.
Why it matters: This advancement has the potential to democratize data access and search functionalities across diverse linguistic and script-based datasets prevalent in India.
A data scientist shares insights from optimizing Pandas workflows, revealing that many seemingly functional codebases harbor significant performance bottlenecks. The article highlights common pitfalls like inefficient row-wise operations and provides strategies for identifying and rectifying these issues, ultimately demonstrating a dramatic 95% reduction in runtime. It also guides readers on recognizing when Pandas itself becomes the limiting factor for complex data tasks.
Key Takeaways
Identify and eliminate inefficient row-wise operations in Pandas.
Understand common performance bottlenecks in typical Pandas usage.
Recognize the limitations of Pandas and know when to explore alternative libraries for better scalability.
Why it matters: This article offers practical, actionable advice for Indian tech professionals working with large datasets, enabling them to significantly improve the efficiency and speed of their data analysis pipelines.
#Pandas#Data Science#Python#Performance Optimization#Big Data
OpenAI has discontinued its specialized Codex coding model, integrating its functionalities into the upcoming GPT-5.5. This move aims to enhance agentic coding capabilities and improve token efficiency, according to the company. The integration signifies a broader trend of consolidating specialized AI models into more generalized, powerful architectures.
Key Takeaways
OpenAI has retired its dedicated Codex AI model for coding.
Codex's capabilities are now integrated into the forthcoming GPT-5.5.
GPT-5.5 is expected to offer improved agentic coding and reduced token consumption.
Why it matters: This strategic consolidation by OpenAI suggests a shift towards more unified and powerful foundational AI models capable of handling diverse tasks, potentially accelerating development cycles and reducing the need for specialized model management.
OpenAI is advising developers not to port existing prompts to GPT-5.5, emphasizing the need to build from a clean slate. The company highlights that legacy prompts are hindering the new model's performance, and that foundational elements like role definitions, previously overlooked by some, are now crucial. This directive suggests GPT-5.5 represents a significant enough architectural shift that old interaction patterns are no longer optimal.
Key Takeaways
Developers must avoid migrating old prompts to GPT-5.5 for optimal performance.
Starting with minimal, fresh prompts for GPT-5.5 is recommended.
Role definitions are re-emphasized as a critical component for effective GPT-5.5 prompting.
Why it matters: This indicates a potentially significant evolution in OpenAI's model architecture, requiring developers to rethink their interaction strategies to fully leverage GPT-5.5's capabilities.
A recent study by The Decoder involved 500 investment bankers evaluating AI-generated content, including outputs from leading models like GPT-5.4 and Claude Opus 4.6. The critical finding is that not a single AI output met the standards for direct client delivery, with many being either too vague or factually incorrect. Despite these shortcomings, over half of the participating bankers indicated a willingness to use the AI-generated material as a foundational first draft for their work.
Key Takeaways
Leading AI models like GPT-5.4 and Claude Opus 4.6 are not yet capable of independently producing client-ready outputs for complex financial tasks.
Investment bankers found AI-generated content to be too imprecise and prone to errors for direct client use.
A majority of bankers see value in AI as a tool to augment their workflow, using its outputs as a starting point for further refinement.
Why it matters: This benchmark highlights the current limitations of AI in high-stakes professional environments like investment banking, underscoring the continued necessity of human oversight and expertise.
A recent survey published by The Decoder indicates a significant trend in the US AI assistant market: users of Anthropic's Claude exhibit a notably higher average income compared to those engaging with competitors like ChatGPT and Google Gemini. This suggests a potential demographic skew where wealthier individuals are disproportionately adopting Claude for their AI needs. The survey analyzed income breakdowns across various AI services, highlighting this distinct user profile for Claude.
Key Takeaways
Claude users in the US report significantly higher weekly incomes than users of other AI assistants.
ChatGPT and Gemini users, while still diverse, show a more varied income distribution compared to Claude.
The survey focuses on the US market and identifies a potential wealth-based segmentation among AI assistant users.
Why it matters: This demographic insight could influence marketing strategies, feature development, and the overall monetization approaches for AI companies targeting affluent user segments.
Contrary to the prevailing narrative of AI agents automating software development and rendering developers obsolete, new research from Chalmers University of Technology and Volvo Group suggests this perspective is flawed. The paper argues that AI agents are not replacing software engineering but rather augmenting and expanding its scope beyond just writing code. This means the future of software engineering will likely involve a deeper integration of AI into various stages of the development lifecycle.
Key Takeaways
AI agents are not poised to eliminate software engineering roles.
The impact of AI is an expansion of the software engineering domain, not a contraction.
Software engineers will likely work alongside AI agents, focusing on broader aspects of development.
Why it matters: This reframes the conversation around AI's impact on tech careers, emphasizing evolution and augmentation rather than displacement.
#AI#Software Engineering#Future of Work#Tech Trends
Anthropic has launched an experimental marketplace where AI agents are acting as both buyers and sellers to conduct real transactions for tangible goods using actual currency. This initiative explores the nascent field of agent-on-agent commerce, demonstrating AI's potential to autonomously engage in economic activity. The platform aims to test the capabilities of AI agents in negotiating, pricing, and completing commercial exchanges in a simulated but real-world environment.
Key Takeaways
AI agents are now capable of autonomously engaging in buying and selling on a functional marketplace.
The experiment involves real goods and real money, moving beyond theoretical demonstrations.
Anthropic is actively researching the future of AI-driven economic interactions and agent autonomy.
Why it matters: This experiment is a significant step towards a future where AI agents can independently participate in and drive economic transactions, potentially revolutionizing online commerce and supply chains.
OpenAI CEO Sam Altman has issued a public apology to the community of Tumbler Ridge, Canada, for the company's failure to notify law enforcement regarding the suspect in a recent mass shooting incident. Altman expressed deep regret for this lapse in communication. This incident raises questions about the responsible handling of potential threats identified by AI systems.
Key Takeaways
OpenAI CEO Sam Altman apologized to the Tumbler Ridge community.
The apology concerns OpenAI's failure to alert authorities about a mass shooting suspect.
This highlights ethical and practical challenges in AI companies' duty to warn.
Why it matters: This incident underscores the critical need for robust protocols and ethical frameworks for AI companies to manage and report potential real-world threats identified by their technologies.
Canadian AI firm Cohere is acquiring German rival Aleph Alpha, backed by Schwarz Group (Lidl's parent company), to create a European-centric AI powerhouse. This merger, with governmental support from both nations, aims to provide a sovereign alternative to US-dominated AI solutions for enterprise clients. The combined entity will focus on enterprise-grade AI, potentially catering to industries seeking data privacy and localized control.
Key Takeaways
Cohere and Aleph Alpha are merging to challenge US dominance in enterprise AI.
Schwarz Group's investment signals significant financial backing for the new venture.
The focus is on providing 'sovereign' AI solutions, appealing to European businesses prioritizing data control and regulatory compliance.
Why it matters: This strategic consolidation represents a significant move to foster independent European AI capabilities and offers Indian tech-savvy readers an alternative to consider in the global AI race.
This Towards Data Science article posits that causal inference in a business context fundamentally diverges from academic approaches due to 'decision-gravity.' This concept suggests that business decisions, unlike scientific experiments, are inherently constrained by existing structures, resources, and strategic goals, creating a unique 'pull' that influences what can be causally investigated and actioned. Consequently, applying standard causal inference techniques directly to business problems requires careful adaptation to account for this practical reality.
Key Takeaways
Business causal inference is distinct from academic research due to 'decision-gravity'.
Decision-gravity represents the practical constraints and directional forces of business operations that shape causal investigations.
Standard causal inference methods need modification to be effective in business settings.
Why it matters: Understanding these differences is crucial for Indian businesses to effectively leverage AI and data science for informed decision-making and strategic advantage.
#causal inference#business analytics#decision making#AI in India
This second part of Towards Data Science's guide dives into extracting actionable insights from document clusters identified in the previous installment. It focuses on unlocking the true potential of these clustered documents by effectively summarizing them to derive meaningful information. The article aims to provide practical methods for tackling massive document summarization.
Key Takeaways
Focuses on deriving actionable information from document clusters.
Builds upon previous steps of document clustering.
Provides methods for effective summarization of large text datasets.
Why it matters: Efficiently processing and summarizing vast amounts of textual data is crucial for data-driven decision-making and gaining competitive advantages in today's information-heavy landscape.
Indian software majors are facing a dual threat: the existential fear of AI disruption impacting their stock performance, and a new wave of top executive departures towards AI frontier companies like OpenAI. This talent drain exacerbates existing market anxieties, as critical leadership and expertise shift to firms at the forefront of AI development, potentially impacting innovation and execution within traditional software companies.
Key Takeaways
Indian software companies are experiencing significant stock declines due to AI disruption fears.
Key executives are now leaving these companies to join leading AI firms such as OpenAI.
This talent exodus poses a substantial challenge to the ongoing operations and future growth of established software players.
Why it matters: This trend signals a critical battle for AI talent, potentially reshaping the competitive landscape for India's vital IT sector.
CNBC tested Elon Musk's xAI chatbot, Grok, integrated with Tesla's Full Self-Driving (Supervised) system during a drive in a Tesla Model Y in New York City. The experiment aimed to evaluate Grok's real-time utility and seamless integration within the vehicle's advanced driving features. While the article likely details specific interactions and observations, the core premise is a hands-on review of this cutting-edge AI's performance in a practical, albeit controlled, automotive environment.
Key Takeaways
Grok was tested for its usability and integration with Tesla's FSD (Supervised) while driving.
The test took place in a Tesla Model Y on the streets of New York City.
The article explores the practical application of an AI chatbot within a vehicle's advanced autonomous driving system.
Why it matters: This hands-on evaluation offers a glimpse into the evolving intersection of conversational AI and automotive technology, potentially shaping future in-car user experiences and autonomous system interactions.
A group of Discord users, reportedly operating as 'sleuths,' managed to gain unauthorized access to Anthropic's internal 'Mythos' research platform. While the full extent of the breach and the specific data compromised are still being investigated, the incident highlights potential vulnerabilities even in sophisticated AI development environments. This news comes amidst a broader report detailing other tech and security concerns, including the exploitation of telecom weaknesses by spy firms and a significant leak of UK health records.
Key Takeaways
Unauthorized access to Anthropic's internal AI research platform 'Mythos' by Discord users.
The incident raises concerns about the security of sensitive AI development data.
Broader tech news includes spy firms exploiting telecom vulnerabilities and a large UK health data leak.
Why it matters: This incident underscores the growing cybersecurity risks surrounding cutting-edge AI research and development, even for prominent players like Anthropic.
Anthropic's AI assistant, Claude, has received new 'Connectors' that enable it to integrate with various everyday applications. This feature allows Claude to access and interact with your existing tools and services, moving beyond just text-based conversations. Imagine Claude helping you manage your calendar, draft emails, or even pull information from your cloud storage – all through these new integrations.
Key Takeaways
Claude now supports integrations with third-party applications and services.
These 'Connectors' expand Claude's utility beyond conversational AI into task automation.
Users can expect Claude to assist with a wider range of daily digital tasks.
Why it matters: This move signifies a crucial step towards making AI assistants more practical and embedded into users' daily workflows, mirroring the trend of intelligent automation gaining traction globally.
OpenAI has reportedly unveiled GPT-5.5, described on Product Hunt AI as their most intelligent and user-friendly model to date. While details are scarce, the announcement suggests a significant advancement in AI capabilities and ease of interaction for users. This iteration promises a more intuitive experience compared to its predecessors.
Key Takeaways
OpenAI's next-generation model, GPT-5.5, is out.
It's being marketed as OpenAI's smartest and most intuitive AI model yet.
This development signals continued rapid progress in large language model technology.
Why it matters: This progression in AI models, particularly in intelligence and usability, has far-reaching implications for innovation across various tech sectors in India and globally.
A new Hollywood production startup, backed by Amazon Web Services (AWS), is leveraging AI to revolutionize filmmaking in Los Angeles. This AI-powered, hybrid model aims to significantly reduce production costs and accelerate filming timelines. The company also anticipates the creation of new jobs within the LA area, potentially reshaping the local industry landscape.
Key Takeaways
AI is being integrated into Hollywood production to improve efficiency and reduce expenses.
AWS is supporting this AI-driven approach to content creation.
The startup's strategy includes job creation in Los Angeles.
This signifies a shift towards tech-centric filmmaking for speed and cost savings.
Why it matters: This development highlights how AI adoption in creative industries can lead to significant economic and operational shifts, potentially influencing content creation workflows globally.
#AI in Hollywood#AWS#Film Production#Tech Innovation#Los Angeles
Isomorphic Labs, a DeepMind spinoff, has announced a significant progress in AI-designed drug discovery, with a pipeline of new medicines ready for human trials. This development signifies a major leap in leveraging artificial intelligence to accelerate and revolutionize the pharmaceutical industry. The company's president shared this optimistic outlook, underscoring the potential of AI in bringing novel treatments to patients faster.
Key Takeaways
DeepMind spinoff Isomorphic Labs is advancing AI-designed drugs towards human clinical trials.
The company claims to have a substantial and promising pipeline of new medications developed using AI.
This announcement highlights the growing impact of AI in accelerating drug discovery and development.
Why it matters: This marks a critical step in validating the efficacy of AI in creating viable drug candidates, potentially transforming the speed and cost of bringing new therapies to market, a significant development for India's burgeoning tech and healthcare sectors.
#AI Drug Discovery#Isomorphic Labs#DeepMind#Clinical Trials#Pharma Tech
MIT scientists have curated the largest-ever collection of Olympiad-level math problems, boasting over 30,000 questions from 47 countries. This extensive dataset is now publicly available, offering AI researchers a more rigorous benchmark for developing advanced mathematical reasoning capabilities. Simultaneously, it serves as an invaluable free resource for students globally preparing for competitive mathematics.
Key Takeaways
MIT has released a massive, open-access dataset of 30,000+ Olympiad-level math problems.
The dataset aims to challenge AI systems in complex mathematical reasoning.
It provides a significant free learning and training resource for students preparing for math competitions worldwide.
Why it matters: This initiative democratizes access to high-quality mathematical challenges, accelerating AI progress in abstract reasoning and empowering aspiring mathematicians across India and beyond.
This Towards Data Science article provides a foundational introduction to approximate solution methods in Reinforcement Learning (RL), a crucial area for tackling complex, real-world problems. It delves into the concept of function approximation, explaining why it's necessary when dealing with large state and action spaces, and explores various choices for approximating the value or policy functions that guide RL agents.
Key Takeaways
Function approximation is essential for scaling RL to problems with vast state/action spaces.
The choice of approximation function significantly impacts RL agent performance and learning efficiency.
Understanding different approximation techniques is key to building more effective RL systems.
Why it matters: Mastering approximation methods is vital for developing advanced AI applications that can learn and adapt in dynamic and complex environments.
Apple is at a critical juncture with AI, and the article argues that the company's next CEO, potentially John Ternus, must deliver a groundbreaking AI product to reclaim its innovative edge. While Tim Cook steered Apple to immense success, he largely missed the AI revolution, leaving a significant gap. This impending leadership change makes a compelling AI offering the absolute top priority to ensure Apple's future relevance and market dominance.
Key Takeaways
Apple's perceived AI lag under Tim Cook necessitates a transformative AI product launch from the next CEO.
John Ternus is identified as the likely successor tasked with this crucial AI mission.
A 'killer AI product' is presented as essential for Apple's continued innovation and competitive standing.
Why it matters: This situation highlights the immense pressure on Apple to pivot decisively into AI, a field where competitors are rapidly advancing, to maintain its position as a tech industry leader.
KDnuggets highlights seven practical use cases for OpenClaw, a tool enabling users to translate AI capabilities into actionable workflows and custom agents. The article demonstrates how OpenClaw is being leveraged to enhance productivity and automate various processes, moving beyond theoretical AI applications to tangible real-world solutions. It emphasizes the platform's ability to empower individuals and businesses to effectively implement and benefit from AI technologies.
Key Takeaways
OpenClaw facilitates the creation of custom AI agents for specific tasks.
The platform offers practical methods for automating complex workflows.
OpenClaw helps in boosting overall productivity by integrating AI into daily operations.
Why it matters: OpenClaw democratizes AI implementation, allowing tech-savvy individuals and businesses in India to readily adopt and benefit from advanced AI functionalities for efficiency and innovation.
Generative AI is rapidly evolving from a creative tool into a formidable weapon for large-scale disinformation and fraud, according to Shuman Ghosemajumder. The InfoQ AI presentation highlights the rise of 'Disinformation Automation,' rendering traditional CAPTCHAs ineffective against AI-driven attacks. Engineering leaders are urged to adopt 'cyber fusion' with a zero-trust approach to combat these sophisticated threats that increasingly mimic human behavior.
Key Takeaways
Generative AI is a dual-use technology with significant potential for malicious applications like disinformation and fraud.
Traditional security measures like CAPTCHAs are becoming obsolete in the face of advanced AI capabilities.
A 'zero-trust' and 'cyber fusion' strategy is essential for organizations to defend against AI-powered automated attacks.
Why it matters: As India continues its digital transformation, understanding and proactively defending against AI-driven disinformation and fraud is critical for maintaining trust and security in the online ecosystem.
A recent viral moment on the red carpet has brought to light a cohort of hyper-realistic AI-generated male influencers on Instagram, often dubbed 'AI thirst traps.' These digital creations, designed to appeal to a sexually-charged audience, are gaining significant traction despite their artificial nature. The creators behind them claim they are often misunderstood, suggesting a growing trend of AI leveraging aesthetics for engagement, even as users remain captivated.
Key Takeaways
AI-generated influencers are becoming a significant presence on social media platforms like Instagram.
These 'AI thirst traps' leverage hyper-realistic visuals to attract a large, often uncritical, audience.
The creators of such AI content feel their work is frequently misinterpreted, highlighting an evolving digital creator landscape.
Why it matters: This phenomenon signals a new frontier in digital content creation and audience engagement, blurring the lines between human and artificial influence in the online world.
#AI Influencers#Deepfakes#Social Media Trends#Content Creation#Digital Art
Vignesh Durai's InfoQ AI article explores building sophisticated agentic and multimodal AI systems by integrating Apache Camel with LangChain4j. The proposed architecture leverages Apache Camel's robust integration capabilities to orchestrate complex workflows involving Large Language Model (LLM) reasoning, Retrieval-Augmented Generation (RAG) for contextually relevant responses, and image classification for handling visual data. This approach allows for the creation of more dynamic and capable AI applications by seamlessly connecting these advanced AI components.
Key Takeaways
Apache Camel can be used to orchestrate complex agentic and multimodal AI workflows.
LangChain4j facilitates integration with LLM reasoning, RAG, and image classification models.
Combining integration frameworks with AI libraries enables advanced AI system development.
Why it matters: This architectural pattern enables developers to build more sophisticated, adaptable, and powerful AI applications by bringing together disparate AI capabilities through a unified integration framework.
Hugging Face has highlighted DeepSeek-V4, a new AI model boasting a massive one million token context window, a significant leap from previous models. This expanded context allows AI agents to process and retain far more information, enabling more complex and nuanced interactions and problem-solving. The key innovation lies in its practical usability, making it a powerful tool for advanced AI applications.
Key Takeaways
DeepSeek-V4 introduces a 1 million token context window, a substantial increase in AI's memory capacity.
The model focuses on practical application, meaning this large context is usable by AI agents for real-world tasks.
This breakthrough enables AI to handle much larger documents, codebases, or conversational histories without losing coherence.
Why it matters: This development pushes the boundaries of what AI agents can accomplish by allowing them to understand and reason over vastly larger amounts of information, paving the way for more sophisticated AI assistants and analytical tools.
#AI#LLM#Context Window#DeepSeek#Hugging Face
Frequently Asked Questions
What is the Daily AI Digest?
The Daily AI Digest is an automated curation of the top 30 artificial intelligence news stories published across the web, summarized for quick reading.
How are these news articles selected?
Our system scans over 50 leading AI research labs, tech publications, and developer forums, evaluating factors like source authority, topic relevance, and community engagement to select the most important stories.
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The daily page is automatically generated every morning, ensuring you wake up to the most critical developments from the previous 24 hours.
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We track a diverse range of sources, including mainstream tech media (like TechCrunch), AI-specific publications (like The Batch), academic institutions (Stanford HAI), and major lab blogs (OpenAI, DeepMind).
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