# Сопутствующие статьи по теме Startup

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Startup", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

Tian Yuandong Announces Startup Venture After Leaving Meta

After leaving Meta, Tian Yuan Dong has announced his new venture. The startup Recursive_SI has officially launched with a list of founders including Tian Yuan Dong. The founding team also comprises Richard Socher (CEO), Tim Rocktäschel, Jeff Clune, Tim Shi, Caiming Xiong, and Alexey Dosovitskiy, among others. These members have experience building AI research labs at companies like Salesforce and Uber, and have held leadership roles at OpenAI, DeepMind, Google Brain, and Meta. Recursive_SI aims to develop artificial intelligence capable of conducting experiments autonomously and safely improving itself through an open-ended, automated scientific discovery process. This is seen as a promising path toward superintelligence. The company has raised $650 million at a valuation of $4.65 billion, led by GV (Google Ventures) and Greycroft, with significant investments from AMD Ventures and NVIDIA. The team has grown to over 25 members, including new additions like Zhuge Mingchen. Zhuge, a Founding Member, holds a Ph.D. in Computer Science from KAUST under Professor Jürgen Schmidhuber. His research focuses on Coding Agents, Recursive Self-Improvement (RSI), and next-generation machine paradigms, with contributions including early RSI systems like GPTSwarm and work on agentic AI frameworks. The founders shared their vision on X: building AI that can automatically discover knowledge and recursively self-improve, fundamentally changing the way science and technology advance. The team is recognized as a leader in core areas of recursive self-improving AI, with past breakthroughs in open-ended algorithms, AI-generated algorithms, automated testing, world models, Vision Transformers, RAG, and AI scientists. There is high anticipation for Recursive_SI's future research.

marsbit05/14 00:26

Tian Yuandong Announces Startup Venture After Leaving Meta

marsbit05/14 00:26

The AI Agent Era Accelerates Its Arrival: Questflow Defines a New Paradigm of Financial Intelligence with On-Chain AI Brokerage

The AI Agent era is accelerating, with the CB Insights AI 100 list highlighting global investment confidence. The focus has shifted from whether AI works to its speed of deployment and ability to manage complex workflows, with autonomous AI Agents driving this transformation. At the forefront is Questflow, a Singapore-based startup redefining financial intelligence through its on-chain AI brokerage. Unlike tools that merely provide data dashboards, Questflow deploys AI Agents that proactively scan markets, form judgments, and execute trades via a conversational interface—operating 24/7 without requiring manual confirmation for each decision. This embodies the new AI paradigm of agents capable of executing multi-step workflows autonomously. Questflow's mission is to democratize institutional-grade trading intelligence. Historically reserved for the ultra-wealthy, this capability is now accessible starting from just $1 through Questflow's "AI Clone + Copy Trade" model. The platform charges only a 1% execution fee, aligning its incentives directly with users and eliminating traditional management or performance fees. The timing is opportune, aligning with key trends identified by CB Insights: the scalable deployment of AI Agents, accelerated AI adoption in financial services, and the maturation of on-chain infrastructure. With robust liquidity on platforms like Hyperliquid and Polymarket, alongside advancements in AI reasoning and non-custodial wallet security, Questflow is positioned to merge the roles of broker, fund, and exchange into a single, accessible platform for millions.

链捕手05/11 13:19

The AI Agent Era Accelerates Its Arrival: Questflow Defines a New Paradigm of Financial Intelligence with On-Chain AI Brokerage

链捕手05/11 13:19

AI Agent Practical Guide: How to Power an Entire Company with Three Intelligent Agents?

AI Agent Implementation Guide: How to Use Three Intelligent Agents to Run an Entire Company? Every solopreneur faces the same bottleneck: too much work for one person, yet not enough revenue to hire three full-time employees at $60,000 each. These roles—market research, content creation, and daily operations—are essential and often consume the founder's time. The smartest entrepreneurs are now "building" AI agents for these jobs instead. Using Claude, MCP servers, and agentic workflows, you can build three specialized AI agents: 1. **Research Agent:** Acts as a full-time market intelligence analyst. It proactively monitors competitors, tracks industry trends, identifies opportunities, and delivers a concise weekly briefing. It requires a knowledge base of competitors and market data, tools like web search APIs and access to your files, and a workflow that runs automatically every Monday. 2. **Content Agent:** Manages your entire content production pipeline from ideation to publishing. It generates topics, drafts content, edits for your specific brand voice, repurposes content across platforms, and schedules posts. Key steps include feeding it your best writing samples to learn your style and implementing quality checks to ensure content meets your standards before you add your unique "soul" to it. 3. **Operations Agent:** Serves as your chief of staff, handling time-consuming administrative tasks like email triage, meeting preparation, and generating weekly reports. By connecting to your email, calendar, and project management tools, it can compress hours of daily work into a 15-minute review. The crucial step is enabling these agents to collaborate as a team. A shared knowledge base allows them to work together; for example, the research agent flags a competitor's new feature, the content agent creates a response, and the operations agent drafts a related email to clients. Financially, three human employees cost around $180,000 annually plus overhead, while three AI agents primarily cost your Claude subscription and setup time. While agents lack human judgment, creativity, and empathy, they can handle 70-80% of the workload for these core roles in a startup's first 12-18 months. The guide recommends building one agent per week: start with research, then content, then operations. In three weeks, you can have a 24/7 AI-powered team instead of working alone.

marsbit05/08 05:49

AI Agent Practical Guide: How to Power an Entire Company with Three Intelligent Agents?

marsbit05/08 05:49

How Many Tokens Away Is Yang Zhilin from the 'Moon Chasing the Light'?

The article explores the intense competition between two leading Chinese AI companies, DeepSeek and Kimi (Moon Dark Side), and the mounting pressure on Yang Zhilin, the founder of Kimi. While DeepSeek re-emerged after 15 months of silence with its powerful V4 model—boasting 1.6 trillion parameters and low-cost, long-context capabilities—Kimi has been focusing on long-context processing and multi-agent systems with its K2.6 model. Yang faces a threefold challenge: technological rivalry, commercialization pressure, and investor expectations. Despite Kimi’s high valuation (reaching $18 billion), its revenue heavily relies on a single product with low paid conversion rates, while DeepSeek’s strategic silence and open-source influence have strengthened its market position and valuation prospects, now targeting over $20 billion. Both companies reflect broader trends in China’s AI ecosystem: Kimi aims for global influence through open-source contributions and agent-based advancements, while DeepSeek prioritizes foundational innovation and hardware independence, notably shifting to Huawei’s chips. Their competition is seen as vital for China’s AI progress, with the gap between top Chinese and U.S. models narrowing to just 2.7% on the Elo rating scale. Ultimately, the article argues that this rivalry, though anxiety-inducing for leaders like Zhilin, is essential for driving innovation and solidifying China’s role in the global AI landscape.

marsbit04/26 11:25

How Many Tokens Away Is Yang Zhilin from the 'Moon Chasing the Light'?

marsbit04/26 11:25

20 Billion Valuation, Alibaba and Tencent Competing to Invest, Whose Money Will Liang Wenfeng Take?

DeepSeek, an AI startup founded by Liang Wenfeng, is reportedly in talks with Alibaba and Tencent for an external funding round that could value the company at over $20 billion. This marks a significant shift, as DeepSeek had previously relied solely on funding from its parent company,幻方量化 (Huanfang Quantitative), and had resisted external investment. The potential valuation would place DeepSeek among the top-tier AI model companies in China, comparable to competitors like MoonDark (valued at ~$18 billion) and ahead of recently listed firms like MiniMax and Zhipu. The funding—which could range from $600 million (for a 3% stake) to $2 billion (for 10%)—is seen as a move to secure resources for model development, retain talent, and support infrastructure needs, particularly as competition in inference models and AI agents intensifies. Both Alibaba and Tencent are eager to invest, not only for financial returns but also to integrate DeepSeek into their broader AI ecosystems. However, DeepSeek’s leadership is cautious about maintaining independence and may prefer financial investors over strategic ones to avoid being locked into a specific tech ecosystem. Alternative options, such as state-backed funds, offer longer-term capital and policy support but may come with slower decision-making and potential constraints on global expansion. With competing AI firms accelerating their IPO plans, DeepSeek’s window for securing optimal terms may be narrowing. The final decision will reflect a trade-off between capital, resources, and strategic independence.

marsbit04/23 09:53

20 Billion Valuation, Alibaba and Tencent Competing to Invest, Whose Money Will Liang Wenfeng Take?

marsbit04/23 09:53

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