文 | 新质动能，作者｜沛林，编辑｜沐风 Llama 4真的作弊刷榜了！ Meta前首席科学家杨立昆（Yann LeCun）近日在采访中证实，团队为优化基准测试结果，对不同评测 使用了不同版本的模型，"结果的确被篡改了一点"。 另一位被裁的FAIR原技术总监田渊栋，则直指Llama 4的研发是"外行领导内行"。 从Llama 3的"开源盟主"到Llama 4的口碑崩塌，不过一年时间。这背后，是Meta内部管理的混乱与技术 路线的摇摆。 随着丑闻曝光与核心团队出走，扎克伯格正推动一场剧烈的转向：高薪挖人、换帅，并彻底放弃开源路 线，转而打造闭源模型"Avocado"。 然而，这款被寄予厚望的新作，却深陷"借鉴"争议——它被曝使用通义千问优化，并试图融合谷歌、 OpenAI等多方技术。 曾经的开源引领者，如今变为闭源的"集大成者"。 2026年，Meta的AI命运，几乎全部压在了这个拼凑而成的Avocado上。如果它再失败，Meta可能将在大 模型的核心赛道上彻底掉队。 Llama 4 作弊了！ 作为图灵奖得主、"卷积神经网络之父"与"深度学习三巨头"之一，杨立昆于2013年受邀加入Meta担任首 席科学家，并成 ...

Key Takeaways AVO leverages avocado specialization and vertical integration to drive volume and global market growth.Dole relies on scale and diversification in fruits and vegetables, balancing bananas with innovative products.Valuation reflects strategy differences, with AVO trading at a premium to DOLE due to higher growth prospects.A few powerful players dominate the global fresh produce space, and Mission Produce Inc. (AVO) and Dole plc (DOLE) stand out for very different reasons. While both operate acr ...

Let's bring in Mark Mahaney, head of internet research at Evercore ISI. Mark, what does this Manis acquisition tell you about Meta's AI strategy. >> Well, I think McKenzie uh uh nailed it.Uh you know, this company is sort of pivoting or extending to get even more aggressive in AI and this has been pretty um part of the course for Zuckerberg. He's uh he's highlighted AI. He's deployed AI aggressively.He's already used it to of the last two to three years to materially improve his ad platform and his user pla ...

Core Insights - Meta Platforms, Inc. (NASDAQ:META) is recognized as one of the best quality stocks to buy before 2026, with significant AI developments expected to be released in that year [1] Group 1: AI Developments - The company is developing a new large language model named Avocado and an image and video generation AI model called Mango, both expected to launch in the first half of 2026 [2] - Meta's chief AI officer, Alexandr Wang, indicated that the new language model will be enhanced for coding capabilities and that the company is in the early stages of developing World Models, which learn about their environment through visual inputs [2] Group 2: Market Sentiment and Financial Outlook - Bank of America reiterated a Buy rating for Meta Platforms, Inc. with a price target of $810, citing the company's 2026 expense guidance and the upcoming LLM launch as key catalysts for positive sentiment [3] - Long-term investors are encouraged to monitor the returns from Meta's significant investments in AI across its core applications, ad monetization, and new ventures [3] Group 3: Strategic Focus - Meta is concentrating on developing AI-powered social platforms and immersive technologies, including Messenger, Instagram, and WhatsApp [4]

​Meta Platforms, Inc. (NASDAQ:META) is one of the Best Quality Stocks to Buy Before 2026. According to a report by The Wall Street Journal released on December 18, Meta Platforms, Inc. (NASDAQ:META) is set to release two new and significant AI developments in 2026. ​The company is developing its next large language model called Avocado, along with a new image and video generation AI model called Mango. The chief AI officer of Meta, Alexandr Wang, noted that these models are expected to be launched in the ...

Group 1: Industry Insights - The competition in large models remains intense, with the Scaling Law still effective. Google's Gemini 3 has made significant advancements in foundational reasoning and multimodal capabilities, while OpenAI's GPT-5.2 emphasizes the potential of large models in creating economic value [1][11][14] - Meta is actively developing two heavyweight AI models, Mango for image and video processing, and Avocado to enhance programming capabilities, indicating a strong commitment to AI development [1][15] - The Chinese open-source model DeepSeek-V3.2 is approaching the performance of top closed-source models, showcasing innovations in sparse attention (DSA), high post-training ratios, and large-scale synthetic data [1][16][18] Group 2: AI Application Acceleration - ByteDance released the Doubao AI mobile assistant, which allows for cross-application autonomous operations, marking a significant evolution in mobile interaction methods [2][26] - The daily token usage of the Doubao model surged from over 16.4 trillion in May 2025 to over 50 trillion by December 2025, reflecting a rapid increase in inference demand [2][28] - NVIDIA's collaboration with Groq, a startup specializing in inference chips, highlights a strategic move towards enhancing inference capabilities while maintaining its dominance in training power [2][29][30] Group 3: Policy and Future Industry Layout - The "14th Five-Year Plan" emphasizes support for strategic emerging industries such as aerospace, quantum technology, and AI, indicating a clear direction for future industrial development [3][42] - The plan also calls for proactive infrastructure development, including information communication networks and integrated computing networks, reinforcing the importance of computational power in the AI era [3][42] Group 4: Related Companies - Key players in computing power include Cambrian, Haiguang Information, and Zhongke Shuguang, among others, indicating a diverse landscape of companies involved in AI and computing infrastructure [4][43] - Companies involved in AI agents include Google, Alibaba, Tencent, and others, showcasing a broad spectrum of firms engaged in AI development [5][44] - In the autonomous driving sector, companies like Jianghuai Automobile and Xiaopeng Motors are notable participants, reflecting the industry's growth [6][45]

Core Viewpoint - By 2025, open-source will dominate the landscape of large models, with a significant increase in the number of users adopting open-source models globally, marking a shift in the competitive dynamics between open and closed-source approaches [1][20]. Group 1: Open-Source vs Closed-Source Dynamics - The debate between open-source and closed-source large models has been ongoing, with both sides presenting strong arguments, but the trend is shifting towards open-source as more major internet companies adopt this approach [1][5]. - Closed-source models, initially seen as the only viable path due to advantages in data security and commercial monetization, are now facing challenges in areas like AI accessibility and ecosystem development [3][10]. - The emergence of open-source models has created a new competitive landscape, with companies like Meta and Alibaba leading the charge in open-source initiatives [5][10]. Group 2: Impact of DeepSeek - The introduction of DeepSeek has significantly altered the competitive balance, demonstrating that open-source models can achieve high performance at lower costs, thus attracting more companies to switch to open-source strategies [7][20]. - DeepSeek's training cost was approximately $294,000, with a training duration of about 80 hours, showcasing a more efficient approach compared to traditional methods [7]. - Open-source models like DeepSeek and Qwen have reportedly matched or even surpassed the performance of leading international products, shifting the focus of competition from pure performance to cost, efficiency, and commercialization capabilities [8][20]. Group 3: Market Trends and User Engagement - The AI application market is rapidly evolving, with mobile and PC active user numbers reaching 729 million and 200 million respectively by September 2025, indicating a shift towards more specialized and efficient applications [11][13]. - Open-source models are seen as the quickest path to market, fostering a collaborative ecosystem that enhances user engagement and accelerates innovation [13][14]. - Companies are increasingly recognizing the long-term commercial value of high user engagement within open-source ecosystems, leading to a competitive race among internet giants to provide comprehensive open-source solutions [15][19]. Group 4: Commercialization of Open-Source - Open-source does not equate to free; companies are exploring various monetization strategies, including enterprise versions, commercial APIs, and cloud services, to sustain their open-source initiatives [18][19]. - Alibaba has open-sourced over 300 models, generating more than 170,000 derivative models, positioning itself as a leader in the global open-source model landscape [16]. - Baidu is integrating its self-developed Kunlun chips with open-source models, adopting a full-stack autonomous approach to enhance its competitive edge [17].

Core Viewpoint - 2025 is expected to be a tumultuous year for Meta, with significant internal challenges and strategic shifts in its AI initiatives [3][4]. Group 1: AI Strategy and Developments - Meta is aggressively pursuing AI advancements, restructuring its AI department around the Meta Superintelligence Labs (MSL) and investing hundreds of billions to compete with rivals like OpenAI and Google [5][6]. - The company is developing new AI models, "Mango" for image and video generation and "Avocado" for advanced code generation, with a planned release in 2026 [12][19]. - Internal issues have plagued the development of the Llama 4 model, which has underperformed and faced multiple delays, leading to concerns about Meta's AI capabilities [16][19]. Group 2: Leadership and Internal Dynamics - CEO Mark Zuckerberg's management style has shifted towards micromanagement, causing internal chaos and dissatisfaction among employees, including key figures like Alexandr Wang [10][31]. - Wang, who was brought in to lead AI initiatives, has expressed frustration over Zuckerberg's tight control, which he believes stifles innovation [31][32]. - The company has seen a wave of executive departures, including long-standing leaders and key AI talent, raising concerns about its internal stability and future direction [40][41]. Group 3: Financial Commitments and Future Outlook - Meta's capital expenditures are projected to reach at least $70 billion in 2025, significantly higher than the previous year's $39 billion, as the company invests heavily in AI infrastructure [48]. - The company has issued a $30 billion corporate bond, one of the largest in U.S. history, to fund its AI initiatives and maintain a competitive edge [53]. - Despite substantial investments, there is uncertainty regarding how Meta will monetize its AI developments, with calls for clearer strategies on integrating AI into its existing business model [57][58].

Key Takeaways AVO is making innovation a core strategy, moving beyond a traditional avocado distributor model.AVO invests in farming, ripening and data tools to manage pricing, promotions and shelf space.AVO's innovation boosts execution but doesn't shield it from weather, pricing cycles or costs.Mission Produce, Inc. (AVO) is growing emphasis on innovation has become a central pillar of its long-term strategy, positioning the company as more than just a traditional avocado distributor. As global fresh-prod ...

来源：环球网 【环球网科技综合报道】12月22日消息，据《华尔街日报》报道，Meta公司正全力以赴在其超级智能 实验室中开发新的人工智能模型。 据悉，该超级智能实验室由Scale AI联合创始人Alexandr Wang领导。目前Meta正在研发一款代号 为"Mango"的图像和视频模型，以及一款内部代号为"Avocado"的新型文本模型。 Wang曾表示，Meta 的目标是让文本模型在代码生成方面表现得更好，同时探索能够理解视觉信息并能 进行推理、计划和行动的新型世界模型，而无需对每一种可能的场景进行预先训练。 外媒称，近年来，Meta在人工智能领域的竞争中落后于OpenAI、Anthropic和谷歌等竞争对手。该公司 人工智能部门今年进行了重大重组，包括领导层变动和从其他顶尖公司挖角研究人员。然而，加入 Meta超级智能实验室的几位研究人员已经离开了公司。 Meta目前还没有一款真正意义上的爆款AI产品。相反，Meta AI助手的用户数量主要得益于该公司庞大 的社交网络，该网络覆盖数十亿用户，因为Meta将该助手嵌入到其应用程序的搜索栏中。这意味着超 级智能实验室将肩负重任。（思瀚） ...