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个人开发者时代崛起,22岁印度开发者搞的业余项目被马斯克Groq看上,如今用户破6万
3 6 Ke· 2025-07-04 08:38
在人工智能技术蓬勃发展的时代,搜索变得比以前更加复杂。谷歌、必应、Reddit、推特、YouTube、学术网站、天气应用上的消息纷繁杂乱,为了找到 一个清晰的答案,很容易在各个网站或应用之间跳来跳去。 为了解决这个问题,年仅 22 岁的孟买开发者 Zaid Mukaddam 开发了一款定位为"Perplexity 替代品"的开源项目,在社区中收获了大量关注。 具体而言,使用这款 AI 搜索引擎时,能干什么?答案是可以在上面搜索网页、X 上的帖子、研究论文、YouTube 视频等。 体验地址:https://scira.ai/ Mukaddam 的故事始于 2024 年 8 月,彼时的 Mukaddam 正处于迷茫期,思考着未来的方向。 此前两个月,他一直在尝试 Vercel AI SDK,但渴望着手更有价值、能产生持久影响力的项目。就在他踌躇之际,父亲的一番话点醒了他:"你为什么不做 点什么?你应该用你的技能做点什么。你无所事事就是在浪费它们。" 这番话促使 Mukaddam 开始积极寻找灵感。 他在 x.com 上浏览时,Perplexity AI 首席执行官 Aravind Srinivas 的一篇文章成 ...
X @Ansem
Ansem 🧸💸· 2025-07-02 15:30
RT Gwart (@GwartyGwart)This is why, paradoxically, I’m almost sympathetic to people who cannot wrap their minds around the “revenue meta.” Not because these people are correct that it’s just a “meta”, they are very wrong and always have been, but because the first 10 years of crypto managed to completely nerdsnipe and indoctrinate so many in this industry into just writing open source code and assuming you’d capture value for ~reasons~ and the worst part was that it was *mainly true* for those 10 years, in ...
李飞飞最新访谈:没有空间智能,AGI就不完整
量子位· 2025-07-02 09:33
Core Viewpoint - The article emphasizes the importance of spatial intelligence in achieving Artificial General Intelligence (AGI), as articulated by AI expert Fei-Fei Li, who believes that understanding and interacting with the 3D world is fundamental to AI development [1][4][29]. Group 1: Spatial Intelligence and AGI - Fei-Fei Li asserts that without spatial intelligence, AGI is incomplete, highlighting the necessity of creating world models that capture the structure and dynamics of the 3D world [29]. - She identifies 3D world modeling as a critical challenge for AI, stating that understanding, generating, reasoning, and acting within a 3D environment are essential problems for AI [7][29]. - The pursuit of spatial intelligence is framed as a lifelong goal for Li, who aims to develop algorithms that can narrate the stories of the world by understanding complex scenes [20][29]. Group 2: Historical Context and Breakthroughs - The article discusses the inception of ImageNet, a pivotal project initiated by Li, which aimed to create a vast dataset for training AI in visual recognition, addressing the data scarcity issue in the early days of AI [11][14]. - The success of ImageNet led to significant advancements in computer vision, particularly with the introduction of AlexNet, which utilized convolutional neural networks and marked a turning point in AI capabilities [19][22]. - Li reflects on the evolution of AI from object recognition to scene understanding, emphasizing the importance of integrating natural language with visual signals to enable AI to describe complex environments [15][20]. Group 3: Future Directions and Applications - Li expresses excitement about the potential applications of spatial intelligence in various fields, including design, architecture, gaming, and robotics, indicating a broad utility for world models [35]. - The article mentions the challenges of data acquisition for spatial intelligence, noting that while language data is abundant online, spatial data is less accessible and often resides within human cognition [33][50]. - Li's new venture, World Labs, aims to tackle these challenges by developing innovative solutions for understanding and generating 3D environments, indicating a commitment to advancing the field of AI [29][35].
AI Agent产品矩阵全景:从RPA到智能体的进化图谱
Sou Hu Cai Jing· 2025-06-30 13:43
在AI技术快速渗透的今天,AI Agent已从实验室走向企业级应用,成为自动化解决方案的核心载体。从字节跳动的"扣子空间"到OpenManus的开源生态,从 AutoGLM的深度思考到实在智能的TARS-RPA-Agent,市面上的AI Agent产品呈现出百花齐放的格局。这些产品不仅定义了技术边界,更在不同场景中重塑 了人机协作的范式。 RPA与AI Agent的融合:从执行到决策的跃迁传统RPA(机器人流程自动化)曾以"规则驱动"为核心,依赖预设流程完成重复性任务。然而,随着AI技术的 成熟,RPA逐渐与AI Agent结合,形成"RPA+AI"的混合自动化模式。例如,Automation Anywhere推出的AI Agent Studio,通过低代码平台允许用户构建自定 义AI Agent,其核心在于将自然语言指令转化为可执行的自动化流程。而实在智能的TARS-RPA-Agent则进一步突破了这一框架,它不仅具备强大的意图理 解能力,还能在复杂操作系统及桌面软件环境下精准操作,甚至能通过"自主感知"调整策略,实现从"执行者"到"决策者"的跃迁。 垂直领域深耕:AI Agent的差异化优势在金融、政务、 ...
China's biggest public AI drop since DeepSeek, Baidu's open source Ernie, is about to hit the market
CNBC· 2025-06-29 16:35
Core Viewpoint - Baidu's decision to open source its Ernie generative AI model marks a significant shift in the AI landscape, potentially increasing competition and altering pricing dynamics in the industry [1][2][3]. Group 1: Baidu's Open Source Strategy - Baidu plans to gradually roll out the open sourcing of its Ernie AI model, a move seen as a major step in the AI race, comparable to the emergence of DeepSeek [1]. - Historically, Baidu has favored a proprietary business model and opposed open-source initiatives, but the success of disruptors like DeepSeek has influenced this change [2]. - The open sourcing of Ernie is expected to elevate industry standards, as major labs releasing powerful models typically raise the competitive bar for the entire sector [3]. Group 2: Impact on Competitors - Baidu's move puts pressure on closed providers like OpenAI and Anthropic to justify their premium pricing and gated APIs [4]. - Industry experts suggest that Baidu's open-source Ernie could disrupt both U.S. and Chinese competitors by offering a powerful alternative at a lower cost [5]. - The CEO of Baidu indicated that the rollout aims to empower developers globally, allowing them to build applications without concerns over model capabilities or costs [6]. Group 3: Market Dynamics and Future Implications - The introduction of open-source models is expected to change cost dynamics in AI model access, enabling more applications to be developed on affordable models [7]. - Baidu's recent ERNIE X1 model reportedly delivers performance comparable to DeepSeek's R1 at half the price, signaling a shift in pricing strategies within the industry [6].
X @Demis Hassabis
Demis Hassabis· 2025-06-27 18:41
RT Google Cloud Tech (@GoogleCloudTech)Gemini CLI ❤️ your ⭐⭐⭐A huge thank you to everyone around the world contributing to this new open source project.If you haven’t already, come build with us → https://t.co/ED2bDraA7d https://t.co/EKBzFerTAA ...
腾讯,大动作!
Zhong Guo Ji Jin Bao· 2025-06-27 15:11
【导读】腾讯混元推出首款开源混合推理模型,擅长Agent工具调用和长文理解 头部互联网公司旗下大模型加速开源。 6月27日,腾讯混元开源的首款混合推理MoE模型Hunyuan-A13B发布,该模型是业界首个13B级别的MoE开源混合推理 模型,其效果比肩同等架构领先开源模型。 开源模型灵活性、透明度和成本优势,为人工智能产业发展带来新机遇。今年年初DeepSeek出圈后,腾讯、阿里、字节 等头部互联网公司旗下大模型开源悄然加速。 腾讯混元开源首款混合推理MoE模型 *加粗为最高分,下划线表示第二名,数据来源于模型各个公开的测试数据集得分 在实际使用场景中,Hunyuan-A13B模型可以根据需要选择思考模式。快思考模式提供简洁、高效的输出;慢思考则涉 及更深、更全面的推理步骤,如反思和回溯。 Hunyuan-A13B模型对个人开发者较为友好,在严格条件下,只需要1张中低端GPU卡即可部署。目前,Hunyuan-A13B已 经融入开源主流推理框架生态,无损支持多种量化格式,在相同输入输出规模上,整体吞吐量是前沿开源模型的2倍以 上。 Hunyuan-A13B集合了腾讯混元在模型预训练、后训练等多个环节的创新技术 ...
How fast are LLM inference engines anyway? — Charles Frye, Modal
AI Engineer· 2025-06-27 10:01
[Music] Thanks everybody for coming. Um, yeah, I wanted to talk about some work I've done recently on trying to figure out uh just how fast these inference engines are when you run open models on them. Uh so the kind of been talking at AI engineer since it was AI engineer summit two years ago. Um and the for a long time it's basically been the like OpenAI rapper conference, right? It's like because just because yeah, what am I going to do? Am I going to run an agent with BERT? Probably not. Um, and that was ...
X @Andy
Andy· 2025-06-27 00:30
RT Fede’s intern 🥊 (@fede_intern)I might be missing something, but as far as I can tell, Ethrex, Nethermind, and Reth already support this with open source implementations. I really respect what Mega is doing, but I’m not sure these numbers are especially surprising in context.With Ethrex, you can launch in L2 mode with a single command and deploy the verifier to reach this level of performance today fully open source.12,000 TPS × 21,000 gas per transfer = 252 mega gas/sec.Is the code from @megaeth_labs ava ...
X @Anthropic
Anthropic· 2025-06-26 16:27
We've also made this open source.You can use .dxt for your own MCP clients as well as contribute to making it work better for your use case: https://t.co/V906Ui2GqF ...