For example I’ve been doing a bunch of late night vibe coding with Gemini 3 in @GoogleAIStudio, and it’s so much fun! I recreated a testbed of my game Theme Park 🎢 that I programmed in the 90s in a matter of hours, down to letting players adjust the amount of salt on the chips! 🍟 (fans of the game will understand the reference 😀) ...

Gemini 3 combines multimodal understanding and coding to help you learn anything. Using Google AI Studio, see how Gemini 3 analyzes a complex research paper on materials science and deep learning to create code for a beautiful, interactive guide with 3D visualizations that make the concepts easy to explore. What will Gemini create if you upload a different paper? Find out more about Gemini 3: https://deepmind.google/models/gemini/ ___ Prompt: I want to learn about ""Scaling deep learning for materials disco ...

Group 1 - Alphabet's stock (GOOGL) surged 11% in a week due to a strong Q3 2025 earnings report that exceeded analyst expectations, significant analyst upgrades, and robust momentum in AI and cloud services [2] - GOOGL's revenue growth of 13.4% over the last 12 months is strong, outperforming AAPL and AMZN, but lagging behind MSFT, META, and Z [7] - GOOGL's operating margin stands at 32.2%, which is high compared to most peers but lower than Microsoft's 46.3% [7] Group 2 - GOOGL's stock has increased by 62.1% in the past year, with a current PE ratio of 27.4, indicating strong performance relative to competitors [7] - A comparative evaluation of GOOGL against key competitors is essential to understand its market position and performance metrics [3][6] - The High Quality Portfolio has outperformed its benchmark, achieving returns exceeding 105% since inception, suggesting a less volatile investment alternative compared to individual stocks like GOOGL [5]

Core Insights - In September 2025, global AI Web Top 100 sites generated approximately 10.135 billion visits, with overseas sites accounting for 91.9% and domestic + overseas combined at 8.1% [1][7] - The traffic is highly concentrated, with the Top 10 sites accounting for 82.2% and the Top 20 for 88.7% of total visits [1][7] - Chatbots dominate the traffic, contributing 76.7% of the total visits [1][7] Global Market Overview - The total web traffic in September reached 10.135 billion visits, with the Top 10 sites capturing 82.2% and the Top 20 capturing 88.7% [7] - The concentration indicates that new players may struggle to gain traction solely through generic traffic, necessitating a focus on specific categories and scenarios for sustainable growth [7] - The primary user behavior on the web revolves around "asking questions—receiving answers/generating content," with tools for rewriting, editing, and formatting being secondary [7] Product Performance - ChatGPT remains the leader in scale but saw a slight increase of only 0.98% [9] - Gemini and Google AI Studio exhibited significant growth, with increases of 46.24% and 64.13% respectively, indicating a resurgence of Google in the web space [9][12] - Perplexity continued to grow steadily at 14.35%, while Grok and JanitorAI experienced declines of 7.44% and 10.01% respectively [11][12] Domestic Market Insights - In the domestic market, web traffic totaled approximately 672 million visits, with the Top 10 sites accounting for 86.9% [4][14] - Chatbots contributed over 60% of the visits, with deepseek leading at 31.759 million visits [14][40] - Notable growth was observed in Qoder (+107%), iFlytek Zhizuo (+90%), and Baidu AI Search (+20%), indicating a strong demand for development tools and visual generation [14][43] Category Trends - The educational, content detection, sales, navigation, and PPT generation categories showed significant month-over-month growth, driven by seasonal factors and structural demand from B-end tools [8][12] - The demand for AIGC in lesson preparation and assignment understanding is becoming normalized, while content detection and rewriting are driven by platform review and content publishing needs [8][12] Emerging Opportunities - New entrants in the market, such as Nano Banana (image editing, +292%), DupDub (text-to-speech, +209%), and Subject.com (education, +279%), are contributing to structural growth despite not being top-tier products [12][30] - The focus on shortening the path from input to usable output is driving user engagement and retention, particularly in the domestic market [41][42]

Group 1 - The AGIX index aims to capture the beta and alphas of the AGI era, representing a significant technological paradigm shift expected to reshape society over the next 20 years, similar to the impact of the internet [2] - The AGIX PM Notes serve as a record of thoughts on the AGI process, inspired by legendary investors like Warren Buffett and Ray Dalio, to witness and participate in this unprecedented technological revolution [2] Group 2 - AGIX has shown a weekly performance of 2.48%, a year-to-date return of 35.13%, and an impressive return of 86.13% since 2024, outperforming major indices like S&P 500 and QQQ [5] - The performance of sectors indicates that the application sector has the highest index weight at 39.77%, followed by infrastructure at 24.93% and semi & hardware at 30.00% [6] Group 3 - Netflix has committed to fully embracing generative AI to enhance production efficiency, despite industry concerns about AI replacing creative roles, with a quarterly revenue growth of 17% to $11.5 billion [19] - Anthropic launched the web version of Claude Code, which has seen a tenfold increase in users since its release, contributing over $500 million in annual revenue [20] - Oracle released AI Database 26ai, integrating AI capabilities deeply into its database stack, allowing semantic searches with a single SQL command [22] Group 4 - The AI infrastructure investment remains strong, with significant deals such as Anthropic's cloud service agreement worth billions and OpenAI's collaboration on a $15 billion data center project [22] - Meta AI's daily active users surged to 2.7 million after launching the 'Vibes' AI video feature, indicating a strong market response [23] - Adobe introduced AI Foundry, allowing enterprises to create customized generative AI models, enhancing brand compliance and output control [24] Group 5 - SAP reported robust Q3 results with total revenue of $10.53 billion, a 11% year-over-year increase, and a 29% rise in net profit to $2.15 billion, despite cloud revenue slightly missing expectations [27] - The differences between ETFs and index funds are highlighted, with ETFs offering real-time trading and lower costs, while index funds provide simplicity and are better suited for long-term investments [28][29]

RT Sundar Pichai (@sundarpichai)Developers - the best image editing + generation model is now GA. Go 🍌🍌🍌 on @GoogleAIStudio + Vertex! ...

RT Google AI Studio (@googleaistudio)https://t.co/v0sO5RN3NI ...

Core Viewpoint - Google DeepMind has introduced the Gemini 2.5 Flash Image model, which features native image generation and editing capabilities, enhancing user interaction through multi-turn dialogue and maintaining scene consistency, marking a significant advancement in state-of-the-art (SOTA) image generation technology [2][30]. Team Behind the Development - Logan Kilpatrick, a senior product manager at Google DeepMind, leads the development of Google AI Studio and Gemini API, previously known for his role at OpenAI and experience at Apple and NASA [6][9]. - Kaushik Shivakumar, a research engineer at Google DeepMind, focuses on robotics and multi-modal learning, contributing to the development of Gemini 2.5 [12][14]. - Robert Riachi, another research engineer, specializes in multi-modal AI models, particularly in image generation and editing, and has worked on the Gemini series [17][20]. - Nicole Brichtova, the visual generation product lead, emphasizes the integration of generative models in various Google products and their potential in creative applications [24][26]. - Mostafa Dehghani, a research scientist, works on machine learning and deep learning, contributing to significant projects like the development of multi-modal models [29]. Technical Highlights of Gemini 2.5 - The model showcases advanced image editing capabilities while maintaining scene consistency, allowing for quick generation of high-quality images [32][34]. - It can creatively interpret vague instructions, enabling users to engage in multi-turn interactions without lengthy prompts [38][46]. - Gemini 2.5 has improved text rendering capabilities, addressing previous shortcomings in generating readable text within images [39][41]. - The model integrates image understanding with generation, enhancing its ability to learn from various modalities, including images, videos, and audio [43][45]. - The introduction of an "interleaved generation mechanism" allows for pixel-level editing through iterative instructions, improving user experience [46][49]. Comparison with Other Models - Gemini aims to integrate all modalities towards achieving artificial general intelligence (AGI), distinguishing itself from Imagen, which focuses on text-to-image tasks [50][51]. - For tasks requiring speed and cost-effectiveness, Imagen remains a suitable choice, while Gemini excels in complex multi-modal workflows and creative scenarios [52]. Future Outlook - The team envisions future models exhibiting higher intelligence, generating results that exceed user expectations even when instructions are not strictly followed [53]. - There is excitement around the potential for future models to produce aesthetically pleasing and functional visual content, such as accurate charts and infographics [53].

Core Viewpoint - The article discusses the emergence of a mysterious AI model named Nano-Banana, which has gained attention for its image generation and editing capabilities, leading to confusion with fake websites claiming to offer its services [1][24]. Group 1 - Nano-Banana was initially discovered on the LMArena platform but has not been officially attributed to any developer [3][4]. - Speculations suggest that Nano-Banana may be a research model from Google, supported by recent social media posts from Google AI personnel [5][7]. - The model excels in text editing, style fusion, and scene understanding, allowing users to upload images and input prompts for element integration [8][9]. Group 2 - Nano-Banana can accurately interpret complex text prompts, demonstrating its ability to manipulate images effectively [9][13]. - The model performs well in commercial scenarios such as product photography and advertising, although it is not without flaws, occasionally producing visual inconsistencies [15][20]. - Users currently have to rely on random experiences through LMArena, as there is no official API or website for Nano-Banana [22][23]. Group 3 - The article includes firsthand evaluations of Nano-Banana's capabilities, comparing its outputs with those from ChatGPT and highlighting its superior performance in generating detailed and contextually appropriate images [30][32]. - Users have experimented with various prompts, showcasing Nano-Banana's versatility in creating images that blend seamlessly with their environments [34][44]. - The integration of Nano-Banana with other tools like Google’s Veo3 is suggested to enhance video production workflows [47][61].

[Music] What if you could automate your life and work, large parts of them, with AI and coding, and as a result, 10x your ambition and human connections. What if you could do that with no prior coding experience at all. And what if that was actually a secret to having a fulfilling life.or at least part of it, maybe just a small part. Over the past two years, I've immersed myself in the world of AI coding and automation. And during that process, I've discovered a few interesting aspects about them, as well a ...