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谷歌×耶鲁联手发布抗癌神器,AI推理精准狙击「隐身」癌细胞
3 6 Ke· 2025-10-17 00:41
刚刚,AI科学应用领域又有一件大事发生! 谷歌与耶鲁大学的科学家们联合发布了一个大模型Cell2Sentence-Scale 27B(C2S-Scale)。 该模型提出了一个关于癌细胞行为的全新假设,并在多次体外实验中得到验证。 这一发现引发广泛关注,它展示了人工智能模型生成原创科学假设的潜力,有望由此打开一条人类抗癌的新途径。 网友prinz在x平台上评价道,「这表明该模型并非简单重复已知事实,而是生成了新的、可验证的科学假设。」 C2S-Scale基于Google的开源Gemma模型构建,训练语料涵盖超过10亿个Token的转录组数据、生物学文献与元数据,从而使其具备跨维度解析细胞行为的 能力。 目前,耶鲁大学的研究团队正在推进AI在其他免疫学情境中生成更多科学预测,这一机制的出现有望加速抗癌新疗法的研发步伐。 研究人员还在bioRxiv上公开了论文的预印本,目前该论文正在经历「同行评审」阶段。 论文地址https://www.biorxiv.org/content/10.1101/2025.04.14.648850v2.full.pdf+html AI不是只懂复现 而其余候选则是从未被报道过的新发现,这 ...
腾讯研究院AI速递 20251017
腾讯研究院· 2025-10-16 23:06
Group 1: Google and AI Models - Google launched the video generation model Veo 3.1, emphasizing enhanced narrative and audio control features, integrating with Gemini API and Vertex AI [1] - The model supports 720p or 1080p resolution at 24fps, with a native duration of 4-8 seconds, extendable up to 148 seconds, capable of synthesizing multi-character scenes with audio-visual synchronization [1] - Users have generated over 275 million videos in Flow, but the quality improvement over Veo 3 is limited, with basic physics performance improved but issues in character performance and complex scheduling remaining [1] Group 2: Anthropic's Claude Haiku 4.5 - Anthropic released the lightweight model Claude Haiku 4.5, offering comparable encoding performance to Claude Sonnet 4 at one-third the cost (1 USD per million input tokens, 5 USD output) and more than doubling inference speed [2] - Scoring 50.7% on OSWorld benchmarks, it surpasses Sonnet 4's 42.2%, and achieves 96.3% in mathematical reasoning tests using Python tools, significantly higher than Sonnet 4's 70.5% [2] - The model targets real-time low-latency tasks like chat assistants and customer service, with a significantly lower incidence of biased behavior compared to other Claude models [2] Group 3: Alibaba's Qwen Chat Memory - Alibaba's Qwen officially launched the Chat Memory feature, allowing AI to record and understand important user information from past conversations, including preferences and task backgrounds [3] - This feature enables personalized recognition across multiple conversations, marking a significant step towards long-term companion AI, unlike short-term context-based memory [3] - Users can view, manage, and delete all memory content, retaining complete control, with the feature initially available on the web version of Qwen Chat [3] Group 4: ByteDance's Voice Models - ByteDance upgraded its Doubao voice synthesis model 2.0 and voice replication model 2.0, enhancing situational understanding and emotional control through Query-Response capabilities [4] - The voice synthesis model offers three modes: default, voice command, and context introduction, allowing control over emotional tone, dialect, speed, and pitch, with automatic context understanding [4] - The voice replication model can accurately reproduce voices of characters like Mickey Mouse and real individuals, achieving nearly 90% accuracy in formula reading tests, optimized for educational scenarios [4] Group 5: Google and Yale's Cancer Research - Google and Yale University jointly released a 27 billion parameter model, Cell2Sentence-Scale (C2S-Scale), based on the Gemma model, proposing a new hypothesis to enhance tumor recognition by the immune system [6] - The model simulated over 4,000 drugs through a dual-environment virtual screening process, identifying the CK2 inhibitor silmitasertib as significantly enhancing antigen presentation only in active immune signal environments, validated in vitro [6] - This research showcases the potential of AI models to generate original scientific hypotheses, potentially opening new avenues for cancer treatment, with the model and code available on Hugging Face and GitHub [6] Group 6: Anthropic's Pre-training Insights - Anthropic's pre-training team leader emphasized the importance of reducing loss functions in pre-training, exploring the balance between pre-training and post-training, and their complementary roles [7] - The current bottleneck in AI research is limited computational resources rather than algorithm breakthroughs, with challenges in effectively utilizing computing power and addressing engineering issues in scaling [7] - The core alignment issue involves ensuring models share human goals, with pre-training and post-training each having advantages, where post-training is suitable for rapid model adjustments [7] Group 7: LangChain and Manus Collaboration - LangChain's founder and Manus's co-founder discussed context engineering, highlighting performance degradation in AI agents executing complex long-term tasks due to context window expansion from numerous tool calls [8] - Effective context engineering involves techniques like offloading, streamlining, retrieval, isolation, and caching to optimally fill context windows, with Manus designing an automated process using multi-layer thresholds [8] - The core design philosophy is to avoid over-engineering context, with significant performance improvements stemming from simplified architecture and trust models, prioritizing context engineering over premature model specialization [8] Group 8: Google Cloud DORA 2025 Report - The Google Cloud DORA 2025 report revealed that 90% of developers use AI in their daily work, with a median usage time of 2 hours, accounting for a quarter of their workday, though only 24% express high trust in AI outputs [9] - AI acts as a magnifying glass rather than a one-way efficiency tool, enhancing efficiency in healthy collaborative cultures but exacerbating issues in problematic environments [9] - The report introduced seven typical team personas and the DORA AI capability model, including user orientation and data availability, which determine a team's evolution from legacy bottlenecks to harmonious efficiency [9] Group 9: NVIDIA's Investment Insights - Jensen Huang reflected on Sequoia's $1 million investment in NVIDIA in 1993, which grew to over $1 trillion in market value, achieving a 1 million times return, emphasizing the importance of first principles in future breakthroughs [10] - The creation of CUDA transformed GPUs from graphics devices to general-purpose acceleration platforms, with the 2012 AlexNet victory in the ImageNet competition marking a pivotal moment, leading to the development of the CUDNN library for faster model training [11] - The core of AI factories lies in system integration rather than chip performance, with future national AI strategies likely to combine imports and domestic construction, making sovereign AI a key aspect of national competition [11]
PayPal: Partnership With Google Might Be A Much-Needed Catalyst
Seeking Alpha· 2025-10-16 19:53
Core Viewpoint - The stock price of PayPal (NASDAQ: PYPL) appreciated by 1%, but it has significantly underperformed the benchmark, yet the bullish thesis remains unchanged [1] Company Performance - Despite the stock price performance, the company is believed to have experienced favorable tailwinds [1] Analyst Background - The analyst has over 10 years of experience in asset management, specializing in equity analysis, macroeconomics, and risk-managed portfolio construction [1] - The analyst has a professional background in both institutional and private client asset management, focusing on equities and derivatives [1] Investment Philosophy - The goal of writing on Seeking Alpha is to share insights, exchange ideas, and promote confidence in long-term investing [1]
Why Tech Growth Could Be Here to Stay
Etftrends· 2025-10-16 19:21
Core Insights - The technology sector has been a significant growth driver for investors over the past few years, dominating the S&P 500 for over two decades [1][2] - Despite concerns about high valuations, the tech sector is expected to continue delivering growth through innovation, particularly in artificial intelligence and cloud computing [2][3] Technology Sector Overview - The tech sector's growth is fueled by ongoing innovation, especially in AI and cloud computing, which raises concerns about whether current valuations can be sustained [2] - The sector is believed to be in a prime position for dynamic growth due to increasing AI adoption and the demand for AI infrastructure [3] Investment Strategy - A large-cap strategy with a focus on the tech sector may provide a viable investment path, exemplified by the Alger Concentrated Equity ETF (CNEQ) [4] - CNEQ is an actively managed fund that aims for long-term growth by maintaining a disciplined portfolio of 30 holdings or fewer, allowing for targeted investment in high-potential companies [5] Fund Composition - As of September 30, 2025, over 50% of CNEQ's portfolio is allocated to the information technology sector, despite being sector-agnostic [6] - CNEQ includes leading tech companies such as Nvidia, Microsoft, Alphabet, and Meta, which are capitalizing on growth opportunities in AI [7] Performance Metrics - CNEQ has shown strong performance, with a year-to-date NAV increase of 36.26% as of October 7, 2025, indicating its potential as a solution for advisors focusing on long-term tech sector growth [9]
Scotiabank Sets New Price Target for Alphabet Inc. (NASDAQ:GOOG)
Financial Modeling Prep· 2025-10-16 19:06
Core Viewpoint - Scotiabank has set a price target of $310 for Alphabet Inc., indicating a potential increase of about 21.31% from its current price of $255.54 [1][2]. Company Performance - Alphabet's current trading price is $255.74, reflecting a 1.60% increase or $4.03 from the previous day [3]. - The stock has experienced a daily trading range between $252.30 and $257.58, with the highest price over the past year being $257.58 and the lowest at $142.66 [3]. Market Position - Alphabet's market capitalization is approximately $3.09 trillion, demonstrating its significant presence in the tech industry [4]. - The trading volume for GOOG is 7,126,721 shares, indicating strong investor interest and activity [4].
The biggest U.S. companies on the S&P 500 spent more than $1 trillion on stock buybacks and dividends in 2024
Fastcompany· 2025-10-16 17:51
LOGIN SUBSCRIBE | FastCo Works advertisement BYÂ Kristin Toussaint Listen to this ArticleMore info 0:00 / 0:00 Microsoft, Nvidia, Apple, Amazon, and Alphabet are the five largest corporations by market cap, with the value of their combined shares totaling more than $16 trillion. These firms each pull in multiple billions of dollars in profit annually, and so pay tens of billions of dollars in annual taxes, too. But like other corporate giants in the S&P 500, the companies are also spending massive amounts o ...
Alphabet: The AI Leader OpenAI Is Still Chasing (NASDAQ:GOOG)
Seeking Alpha· 2025-10-16 17:30
When Elon Musk, Sam Altman, and others co-founded OpenAI back in 2015 they said the reason was to create a non-profit to develop artificial intelligence "in the way that is most likely to benefit humanity as aMichael Fitzsimmons is a retired electronics engineer and avid investor. He advises investors to construct a well-diversified portfolio built on a core foundation of a high-quality low-cost S&P500 fund. For investors who can tolerate short-term risks, he advises an over-weight position in the technolog ...
Alphabet: The AI Leader OpenAI Is Still Chasing (But Will Never Catch)
Seeking Alpha· 2025-10-16 17:30
Group 1 - The article discusses the founding of OpenAI in 2015 by Elon Musk, Sam Altman, and others, with the aim of developing artificial intelligence to benefit humanity [1] - Michael Fitzsimmons, a retired electronics engineer and investor, recommends constructing a diversified portfolio centered around a low-cost S&P 500 fund [1] - Fitzsimmons suggests an overweight position in the technology sector for investors who can tolerate short-term risks, as he believes it is in the early stages of a long-term bull market [1] - For dividend income, Fitzsimmons advises considering large oil and gas companies that offer strong dividend income and growth [1] - The article emphasizes a top-down capital allocation approach tailored to individual investor situations, including factors like age, risk tolerance, and financial goals [1]
7 Driverless Vehicle Stocks That Could Set You Up for Life
Yahoo Finance· 2025-10-16 17:08
Core Insights - Nvidia has established itself as a dominant player in the GPU market, with significant growth expected in its automotive business, projected to reach nearly $11 billion by 2035 at a 20% CAGR [1] - Amazon's acquisition of Zoox aims to develop fully autonomous electric vehicles, leveraging its logistics network for urban ride-hailing services [2] - Alphabet's Waymo is recognized as a leader in the driverless vehicle sector, offering Level 4 robotaxi services and benefiting from substantial financial backing and technological expertise [3] Industry Overview - The driverless vehicle market is anticipated to experience explosive growth over the next two decades, potentially reaching trillions of dollars by 2030, driven by technological advancements and safety improvements [6] - Major traditional automakers and technology companies are heavily investing in driverless vehicle technology, indicating a robust competitive landscape [5] Key Companies - Mobileye Global is positioned as a critical partner in the development of robotaxis, providing Advanced Driver Assistance Systems (ADAS) and various driverless vehicle technologies [8] - Uber Technologies is launching a global robotaxi program in 2026, utilizing Lucid's vehicle architecture and Nuro's Level 4 autonomy system [9] - Hesai Group is a leader in lidar technology, essential for various applications in autonomous vehicles, and has secured design wins with multiple automakers [11] Emerging Technologies - QuantumScape focuses on developing solid-state lithium-metal batteries for electric vehicles, which are expected to play a crucial role in the future of driverless vehicles [12] Investment Considerations - The driverless vehicle industry is set for significant transformation, with multiple companies positioned to benefit as the market evolves [13]
Alphabet: Best Stock To Own In An AI Recession
Seeking Alpha· 2025-10-16 16:21
But that doesn't mean that investors aren't getting ahead of themselves when it comes to expectations and valuations.The Pragmatic Investor covers global macro, international equities, commodities, tech and cryptocurrencies and is designed to guide investors of all levels in their journey. Features include a The Pragmatic Investor Portfolio, weekly market update newsletter, actionable trades, technical analysis, and a chat room. Learn moreJames Foord is an economist by trade and has been analyzing global ma ...