hodler

23 Apr 2026, 10:21

The DAT collapse: Pantera wants Satsuma to dump its bitcoin as shares crash 99%

Pantera Capital is urging London-listed Satsuma Technology to liquidate its remaining bitcoin holdings and return cash to shareholders.

22 Apr 2026, 19:40

DeepSeek is seeking funding at a valuation above $20 billion

DeepSeek is now chasing a valuation above $20 billion as Tencent Holdings and Alibaba Group discuss possible investments in the Chinese AI startup. The Information reported that on Wednesday, citing four people who knew about the talks. DeepSeek, which is owned by hedge fund High-Flyer Capital Management, had only just started talking to outside investors for the first time. By Friday, the reported target was at least $300 million at a valuation of at least $10 billion. Now the asking price has climbed fast as interest builds around DeepSeek. The talks are still going on, so the final number could still change. The amount DeepSeek wants to raise could also change. Some U.S. venture capital companies may be cautious because DeepSeek is a Chinese startup. Earlier this year, Cryptopolitan reported that DeepSeek did not show U.S. chipmakers its flagship model for performance tuning. We also reported that one of DeepSeek’s newer models was trained on Nvidia’s most advanced banned chip. Back in January 2025, the first big DeepSeek release helped trigger a global tech selloff and pushed Chinese rivals to upgrade their own models. Tencent and Alibaba push DeepSeek into a bigger money race Meanwhile, on the Dwarkesh Podcast on Wednesday, Nvidia chief executive Jensen Huang said it would be “a horrible outcome” for the United States if DeepSeek optimized its new AI models to run on Huawei chips instead of American hardware. Jensen said, “If future AI models are optimised in a very different way than the American tech stack,” and as “AI diffuses out into the rest of the world” with Chinese standards and technology, China “will become superior to” the United States. On chip performance alone, Huawei still trails Nvidia. The Ascend 910C, which came before the 950PR, delivers about 60% of the inference performance of Nvidia’s H100. That H100 is already two generations behind Nvidia’s current best chip. American chips are about five times more powerful than Chinese rivals today, and that gap is expected to widen to 17 times by 2027. Huawei is targeting 750,000 AI chip shipments in 2026, but its total production amounts to only about 3% to 5% of Nvidia’s combined computing power. “A lot of work has to go into it to change. But go to the global south, go to the Middle East. Coming out of the box, if all of the AI models run best on somebody else’s tech stack, you’ve got to be arguing some ridiculous claim right now that that’s a good thing for the United States,” said Jensen. AI funding surges as DeepSeek and Vast Data chase bigger checks Jensen said his real concern is not just the gap in chip strength. He said China could still catch up in AI because it has “abundant energy” and a “large pool of AI researchers.” If DeepSeek V4 runs well on Ascend chips, that would give China another route in AI development that does not depend on Nvidia across the supply chain. That same funding rush showed up elsewhere on Wednesday. Vast Data announced a $1 billion funding round at a $30 billion valuation, and Nvidia was one of the backers. The company says it supports projects that power millions of GPUs. Its customers include CoreWeave, Mistral, the U.S. Air Force, and Cursor. The new round more than tripled Vast’s $9.1 billion valuation from 2023. Drive Capital and Access Industries led the Series F. Fidelity Management and Research Co., NEA, and Nvidia also joined. The financing included both primary and secondary capital. Dealroom said AI companies globally have already raised $280.5 billion this year, with more than $170 billion going to OpenAI, Anthropic, and xAI. Chris Olsen of Drive Capital said, “The scale and speed of AI adoption are creating a new class of infrastructure company.” Chris added, “VAST is emerging as the clear leader in this category, with the architecture and momentum to support the world’s most demanding AI environments.” The smartest crypto minds already read our newsletter. Want in? Join them .

22 Apr 2026, 19:05

Ex-Ripple CTO Schwartz Says Chris Larsen Gifts Me Trip Tickets to Antarctica, XRP Army Reacts

Crypto communities often transform even casual personal anecdotes into layered narratives, especially when those stories involve influential figures in major blockchain ecosystems. Within the XRP community, executives and developers often become focal points for speculation, with everyday events quickly turning into symbolic debates about the network’s future and culture. That dynamic resurfaced after XRP ecosystem observer Vet shared details on X, highlighting an unusual story involving Ripple co-founder Chris Larsen and Ripple’s former Chief Technology Officer David Schwartz . In Vet’s post, Schwartz explained how Larsen’s investment in a telescope company indirectly led to an unexpected trip to Antarctica, an anecdote that later spread widely across the XRP community. The Antarctic Trip Originates From a Telescope Investment In a video clip referenced by Vet, Schwartz explained that Chris Larsen invested in a company that manufactures telescopes. He noted that he did not fully understand Larsen’s motivation for the investment but confirmed that the arrangement later included travel benefits for investors. Chris Larsen got Antarctica trip tickets as an investor of a company that makes telescopes. He couldn't go and gifted David and his wife the tickets. pic.twitter.com/5ndjwqwDqJ — Vet (@Vet_X0) April 22, 2026 Schwartz stated that the company organized a cruise expedition to Antarctica connected to a rare eclipse visible primarily from polar regions. The cruise operator provided tickets to investors as part of the broader arrangement tied to the event. According to Schwartz, Larsen initially planned to attend the expedition but ultimately could not go. Larsen then contacted Schwartz well in advance of the trip and offered him and his wife the tickets instead. Schwartz accepted the invitation and described the experience as a long-planned Antarctic cruise associated with the eclipse event. XRP Community Interprets Symbolic Connections Following Vet’s post, XRP community members were quick to draw symbolic connections between the anecdote and recurring motifs in XRP-related discussions. Users referenced themes such as telescopes, glaciers, and polar imagery, which frequently appear in XRP community posts and visual interpretations. Some participants connected the story to earlier images and comments from Schwartz featuring icy landscapes and abstract symbolism. Others framed the anecdote as part of a broader pattern of metaphorical storytelling that often surrounds Ripple executives and long-term XRP discourse. We are on X, follow us to connect with us :- @TimesTabloid1 — TimesTabloid (@TimesTabloid1) June 15, 2025 Community Reaction Highlights Narrative-Driven Culture The response from XRP supporters reflected a well-established pattern within the community: the tendency to interpret real-world events through symbolic or thematic lenses. One user described Schwartz metaphorically as “the Bear,” suggesting he represents deeper infrastructure work within a future financial system built on blockchain technology. Another commenter argued that symbolic “riddles” appear frequently across XRP discussions, referencing recurring motifs such as telescopes, castles, and coded imagery that circulate widely on social platforms. These interpretations demonstrate how XRP supporters often merge technical development discussions with narrative frameworks that assign broader meaning to public statements and personal stories. Between Anecdote and Interpretation While Schwartz’s account clearly describes a personal travel experience linked to an investment perk, the XRP community has expanded the story into a wider symbolic conversation. Vet’s report highlights how quickly informal anecdotes about Ripple figures can turn into interpretive narratives within highly engaged crypto communities. In this case, an Antarctic cruise invitation has become another example of how XRP discourse often blends real-world events with cultural storytelling, reinforcing the community’s strong tendency toward narrative construction around ecosystem figures and developments. Disclaimer : This content is meant to inform and should not be considered financial advice. The views expressed in this article may include the author’s personal opinions and do not represent Times Tabloid’s opinion. Readers are urged to do in-depth research before making any investment decisions. Any action taken by the reader is strictly at their own risk. Times Tabloid is not responsible for any financial losses. Follow us on Twitter , Facebook , Telegram , and Google News The post Ex-Ripple CTO Schwartz Says Chris Larsen Gifts Me Trip Tickets to Antarctica, XRP Army Reacts appeared first on Times Tabloid .

22 Apr 2026, 17:55

Google Chrome AI Transforms the Browser into a Revolutionary Enterprise Coworker

BitcoinWorld Google Chrome AI Transforms the Browser into a Revolutionary Enterprise Coworker In a significant move to redefine workplace productivity, Google announced at its Cloud Next event in San Francisco on April 30 that it is embedding advanced, agentic AI directly into Chrome, effectively turning the world’s most popular browser into an intelligent coworker for enterprise users. This strategic integration of its Gemini AI aims to automate routine web-based tasks, promising to reshape daily workflows for millions of professionals. Google Chrome AI Introduces ‘Auto Browse’ for the Enterprise Google’s new “auto browse” feature represents a major leap in practical AI application. Consequently, this functionality allows Chrome to understand the live context of a user’s open browser tabs using Gemini. Subsequently, the AI can execute a range of actions based on that context. For instance, it can book travel, input data into forms, schedule meetings, and manage other repetitive web-based work. The company demonstrated several potential use cases during its announcement. These examples include populating a company’s CRM from a Google Doc, comparing vendor pricing across multiple tabs, and summarizing a job candidate’s portfolio. Furthermore, the system can extract key data from a competitor’s product page. Importantly, Google emphasizes a “human in the loop” requirement. Therefore, users must manually review and confirm all AI suggestions before any final action occurs. This design philosophy aims to augment human workers rather than replace them. The Evolving Landscape of AI-Powered Workflows This development is part of a broader industry trend where AI is shifting from a conversational tool to an active agent. Previously, AI assistants like chatbots required detailed, step-by-step instructions. Now, agentic AI can perceive a digital environment and take multi-step actions to achieve a goal. Google’s implementation within Chrome places this powerful capability directly into a fundamental work tool used by over 3 billion people globally. The initial rollout will target Workspace users in the United States. Administrators can enable the feature via policy controls. Google has also made a critical data privacy assurance. Specifically, an organization’s prompts and data will not train Google’s public AI models. This commitment addresses growing enterprise concerns about data sovereignty and intellectual property. Balancing Productivity Promises with Workplace Realities Google positions the tool as a way to accelerate tedious tasks, thereby freeing employees for more strategic, creative work. However, this promise intersects with ongoing debates about AI’s actual impact on work intensity. Several independent studies, including research from Stanford University and the MIT Sloan School of Management, suggest AI often increases the pace and volume of work rather than reducing total hours. At the enterprise level, this dynamic could lead managers to expect higher output. The success of tools like auto browse may therefore depend on corporate culture and whether saved time is reinvested in innovation or simply absorbed by increased workload expectations. Google’s approach of requiring human approval seeks to maintain oversight, but it also introduces a new step in the workflow that users must manage. Enhanced Security and the Crackdown on ‘Shadow AI’ Alongside the productivity features, Google announced expanded security measures within Chrome Enterprise Premium. A new “Shadow IT risk detection” capability will help IT teams identify unsanctioned AI tools and compromised browser extensions. This system scans for “anomalous agent activity” across an organization’s browser ecosystem. While framed as a critical security feature, this also allows Google to leverage corporate IT policy to consolidate its position as the primary AI provider within enterprises. Historically, many successful workplace tools, like early cloud storage and collaborative docs, gained traction through grassroots, employee-led adoption—a phenomenon once called “Enterprise 2.0.” Google’s new controls aim to give administrators visibility and control over similar organic adoption of competing AI agents. Key Security Upgrades Include: Detection of unsanctioned Gen AI and SaaS site usage. AI-powered “Gemini Summaries” of Chrome Enterprise release notes for IT teams. An expanded partnership with Okta to reduce session hijacking risks. New integration with Microsoft Information Protection (MIP) for consistent policy enforcement. Practical Implementation: Skills and User Interface For end-users, the AI will operate through customizable “Skills.” These are saved workflows for common tasks. Users can activate a Skill by typing a forward slash (“/”) or clicking a plus icon within the Chrome interface. This design mirrors shortcuts in modern productivity software, aiming for a low-friction user experience. The ability to create and reuse these Skills is intended to provide personalized automation that adapts to specific job functions, from sales and recruiting to procurement and research. The feature’s success will hinge on its reliability and the intuitiveness of Skill creation. If the AI misinterprets context or makes errors in data entry, the required human review process could become a bottleneck, negating time-saving benefits. Google’s challenge will be to train Gemini on the vast and varied structure of the web to ensure high accuracy across different websites and web applications. Conclusion Google’s transformation of Chrome into an AI coworker marks a pivotal moment in enterprise software. By embedding agentic capabilities directly into the browser, Google is placing AI at the center of the digital workflow. The dual focus on productivity via “auto browse” and control through enhanced security reflects the complex realities of modern IT management. While the promise of regained time is compelling, the ultimate impact of this Google Chrome AI integration will depend on its execution, adoption, and the evolving relationship between human workers and their automated assistants. The enterprise browser has now become an active participant in the workday. FAQs Q1: What is Google’s new “auto browse” feature in Chrome? The “auto browse” feature is an agentic AI capability that allows Google’s Gemini AI to understand the context of your open browser tabs and perform tasks like data entry, scheduling, and comparison shopping automatically, with mandatory human review before final action. Q2: Who will have access to the AI features in Chrome first? The features will initially roll out to Google Workspace enterprise users in the United States. Access is controlled by IT administrators through policy settings. Q3: How does Google address data privacy with this workplace AI? Google states that an organization’s prompts, data, and usage of the AI features within Chrome will not be used to train or improve its public Gemini AI models, addressing a key enterprise concern. Q4: What are “Skills” in the context of Chrome’s new AI? “Skills” are user-defined, saved workflows for common web-based tasks. Users can trigger them quickly with a forward slash (“/”) command, allowing for personalized automation of repetitive processes. Q5: What security features did Google announce alongside the AI tools? Google introduced “Shadow IT risk detection” in Chrome Enterprise Premium to identify unsanctioned AI tool usage, enhanced extension security controls, and a deeper integration with Okta and Microsoft Information Protection to secure the agentic workplace. This post Google Chrome AI Transforms the Browser into a Revolutionary Enterprise Coworker first appeared on BitcoinWorld .

22 Apr 2026, 17:50

AI Drug Discovery Breakthrough: 10x Science Unlocks the Protein Characterization Bottleneck with $4.8M Funding

BitcoinWorld AI Drug Discovery Breakthrough: 10x Science Unlocks the Protein Characterization Bottleneck with $4.8M Funding In a significant move for the biotechnology sector, startup 10x Science has secured $4.8 million in seed funding to address a critical bottleneck in AI-driven drug discovery. Founded in December 2025, the company aims to transform how researchers characterize the flood of potential drug candidates generated by artificial intelligence models. This development, announced from San Francisco, CA, on April 30, highlights a pivotal shift from prediction to practical analysis in the race to develop new therapeutics. The AI Drug Discovery Bottleneck Artificial intelligence has revolutionized early-stage drug development, particularly through tools like Google DeepMind’s AlphaFold, which predicts protein structures with unprecedented accuracy. Consequently, AI models can now generate thousands of potential drug molecule candidates. However, a major impediment remains. Researchers must physically test and characterize each candidate to understand its real-world properties, a slow and resource-intensive process known as the characterization bottleneck. “You can add as many candidates as you want to the top of the funnel, but they all have to pass through this characterization process,” explained David Roberts, co-founder of 10x Science. “Everything needs to be measured.” This step is non-negotiable for regulatory approval and mass production, creating a significant logjam. For biologic drugs—complex medicines produced in living cells—understanding a protein’s precise structure is fundamental to ensuring it safely and effectively targets diseases like cancer. The Core Challenge: Mass Spectrometry Data The gold standard for molecular analysis is mass spectrometry. This technique measures molecules in an electric field to determine their atomic makeup. While powerful, it generates immensely complex datasets. Interpreting this data requires rare expertise and consumes vast amounts of a scientist’s time, slowing the entire drug development pipeline. The founders of 10x Science, Roberts, Andrew Reiter, and Vishnu Tejas, experienced this frustration firsthand while researching cancer immunology in a Stanford University lab. 10x Science’s AI-Powered Platform 10x Science’s solution is a proprietary software platform that merges deterministic algorithms from chemistry and biology with specialized AI agents. These agents are trained to interpret mass spectrometry data intelligently and traceably. A key innovation is the platform’s ability to make its analytical reasoning transparent, a crucial feature for regulatory compliance in the pharmaceutical industry. The platform’s practical impact is already being felt. Matthew Crawford, a scientist at Rilas Technologies, has used the software for several weeks. “I ran a particular protein through it, and it just kind of figured out, from what I named the file, what the protein probably was,” Crawford noted. The AI then autonomously searched online databases for the protein’s sequence, saving manual input time. Crawford praised the tool for making reasonable assumptions and providing clear explanations, attributing its effectiveness to the deep domain knowledge of its creators. Key capabilities of the 10x platform include: Autonomous data sourcing and sequence identification. Traceable analysis for audit and compliance trails. Adaptability to evaluate diverse molecule types. Funding, Traction, and Strategic Vision The $4.8 million seed round was led by Initialized Capital, with participation from Y Combinator, Civilization Ventures, and Founder Factor. The capital will fuel engineering hires and further model refinement. Significantly, 10x is already working with multiple major pharmaceutical companies and academic institutions, indicating strong early market validation. For investors, the company represents a unique proposition. “This is a SaaS platform that pharma has to pay for, every single month, to go through all of these potential candidates,” said Zoe Perret, a partner at Initialized. This model offers exposure to the biotech sector without the binary risk of a single drug’s clinical success. The founders’ specialized expertise in both biochemistry and AI presents a formidable barrier to entry for potential competitors. Beyond Characterization: A New Molecular Intelligence The company’s ambitions extend beyond streamlining a single process. Roberts envisions creating a new paradigm for understanding biology. “The deeper thing behind what we’re building is actually a new way to define molecular intelligence,” he stated. The long-term goal is to integrate protein structure data with other cellular information, providing a more holistic and dynamic view of biological systems to accelerate discovery. Conclusion The launch of 10x Science marks a critical evolution in AI drug discovery. By directly tackling the characterization bottleneck with a sophisticated, AI-powered platform, the startup is enabling researchers to validate AI-generated candidates faster and more reliably. This advancement not only accelerates the drug development timeline but also democratizes access to complex analytical techniques. As AI continues to generate a deluge of potential therapeutics, tools like those from 10x Science will be indispensable for translating digital promise into tangible, life-saving medicines. FAQs Q1: What is the main problem 10x Science is solving? 10x Science addresses the “characterization bottleneck” in AI drug discovery. While AI can rapidly generate thousands of potential drug candidates, physically testing and analyzing each one’s properties using techniques like mass spectrometry is slow, expensive, and requires rare expertise. Q2: How does the 10x Science platform work? The platform combines established scientific algorithms with AI agents specifically trained to interpret complex mass spectrometry data. It automates data analysis, provides traceable reasoning for compliance, and can autonomously source relevant information, significantly speeding up the characterization process. Q3: Who are the founders of 10x Science? The company was founded by David Roberts and Andrew Reiter, both experienced biochemists, and Vishnu Tejas, a serial founder with computer science and AI expertise. The trio previously collaborated in the Stanford lab of Nobel laureate Dr. Carolyn Bertozzi. Q4: Why is this important for the future of drug development? By making characterization faster and more accessible, 10x Science’s technology helps bridge the gap between AI-generated hypotheses and real-world testing. This can drastically shorten development timelines, reduce costs, and allow researchers to focus on the most promising candidates, potentially bringing new treatments to patients sooner. Q5: What is the business model for 10x Science? 10x Science operates on a Software-as-a-Service (SaaS) model. Pharmaceutical companies, biotech firms, and academic labs pay a recurring subscription fee to access the platform, providing a scalable revenue stream that is not dependent on the success of any single drug. This post AI Drug Discovery Breakthrough: 10x Science Unlocks the Protein Characterization Bottleneck with $4.8M Funding first appeared on BitcoinWorld .

22 Apr 2026, 17:05

60% of SWIFT Listed Banks Are Ripple (XRP) Related

Global payments infrastructure is undergoing a quiet but structural transformation as traditional banking rails gradually converge with blockchain-based settlement systems. Instead of replacing legacy networks, financial institutions now build layered payment architectures that combine SWIFT messaging, regional clearing systems, and emerging distributed ledger technologies. This shift has intensified debate over how deeply blockchain networks—particularly Ripple’s ecosystem—are embedding into mainstream finance. That debate gained renewed attention after analyst Diana shared a post on X highlighting what she described as significant overlap between SWIFT-listed banks and Ripple-related infrastructure . According to Diana, a recent SWIFT framework announcement referenced more than 50 supporting banks, many of which already maintain operational or exploratory ties to Ripple through custody services, payment integrations, or RippleNet participation. Expanding Overlap Between SWIFT Banks and Ripple Systems Diana’s analysis suggests that roughly 60% of banks operating under the SWIFT framework now have some form of Ripple connection . These connections vary in scope, ranging from pilot integrations and cross-border payment testing to direct engagement with RippleNet and related blockchain payment tools. This overlap reflects a broader industry trend in which banks avoid single-network dependency. Instead, they operate across multiple payment rails, selecting systems based on transaction cost, speed, regulatory requirements, and counterparty compatibility. 60% of SWIFT listed banks are Ripple-related… Probably nothing… https://t.co/yOGHEhxcOO pic.twitter.com/DKJsF6BVOu — Diana (@InvestWithD) April 21, 2026 As a result, financial institutions increasingly treat blockchain networks as supplementary infrastructure rather than disruptive replacements. SWIFT’s Blockchain Strategy and Industry Transition The reported overlap coincides with SWIFT’s ongoing development of a blockchain-based ledger designed to modernize cross-border payments. The initiative, expected to expand through 2026, signals SWIFT’s intention to integrate distributed ledger technology into its long-established global messaging framework. Diana described this approach as a “parallel track” strategy. Under this model, SWIFT continues to support its legacy infrastructure while simultaneously introducing blockchain-enabled settlement capabilities. This allows banks to adopt new technology incrementally without abandoning existing compliance and operational systems. The strategy also reflects growing pressure on global payment networks to reduce settlement delays, improve transparency, and enhance liquidity efficiency. We are on X, follow us to connect with us :- @TimesTabloid1 — TimesTabloid (@TimesTabloid1) June 15, 2025 Ripple’s Role in a Multi-Rail Banking Environment Within this evolving system, Ripple’s technology stack continues to appear in discussions around cross-border settlement optimization . Banks that engage with RippleNet or related infrastructure often do so to improve transaction speed or reduce foreign exchange friction in international payments. In this environment, XRP frequently enters the conversation as a potential liquidity bridge asset. Adoption levels differ across institutions, but its design suits use cases that require fast value transfer between currencies and banking systems. Rather than operating as a standalone alternative to SWIFT, Ripple’s ecosystem increasingly fits into a broader interoperability framework that connects multiple financial networks. A Converging Global Payment System The reported 60% overlap between SWIFT-listed banks and Ripple-related systems highlights a broader convergence in global finance. Instead of a binary competition between legacy banking and blockchain, the industry appears to be building an interconnected model where both systems coexist and interact. If this trajectory continues, XRP’s long-term relevance may emerge less from disruption and more from integration—positioning it as a liquidity layer within an increasingly hybrid global financial infrastructure. Disclaimer : This content is meant to inform and should not be considered financial advice. The views expressed in this article may include the author’s personal opinions and do not represent Times Tabloid’s opinion. Readers are urged to do in-depth research before making any investment decisions. Any action taken by the reader is strictly at their own risk. Times Tabloid is not responsible for any financial losses. Follow us on Twitter , Facebook , Telegram , and Google News The post 60% of SWIFT Listed Banks Are Ripple (XRP) Related appeared first on Times Tabloid .