RT Demis Hassabis (@demishassabis)@GoogleDeepMind has led the way in applying AI to science. Great to see the White House’s new Genesis Mission & excited to be collaborating with @ENERGY by giving National Lab scientists accelerated access to our frontier AI models & agentic tools, starting with AI co-scientist. ...

Innovation & Discovery - Isomorphic Labs is experiencing monthly breakthroughs, indicating a rapid pace of innovation [1] - The company emphasizes being at the "frontier" of discovery, highlighting its focus on cutting-edge research [1] Leadership & Vision - Isomorphic Labs' CEO Demis Hassabis discussed the company's progress on the Google DeepMind podcast [1] - The CEO's statement reflects a sense of accomplishment and excitement about the company's direction [1]

Always enjoy discussing the big picture with @FryRsquared. We talked about the frontiers of computability, the nature of the mind, and why I’m optimistic that AI will help us understand the universe’s deepest mysteries.+ this wraps up another season of the award-winning @GoogleDeepMind Podcast - huge congrats to the team!Google DeepMind (@GoogleDeepMind):We’re using AI to work on root node problems – fundamental scientific challenges that unlock societal benefits. 🧪From fusion and superconductors to entirel ...

Core Viewpoint - The recent launch of GWM Worlds and GWM Robotics by Runway pushes video generation towards an interactive "world simulation" paradigm, reigniting discussions on the definition and scope of "world models" as interfaces for creation and interaction, simulators for training and evaluation, or cognitive frameworks for reasoning and decision-making [1]. Group 1: Evolution of World Models - Over the past two years, world models have evolved to be considered on par with LLMs in the AGI landscape, transitioning from a narrow definition focused on reinforcement learning to a broader understanding that includes generative modeling [4]. - Initially, world models were seen as internal environment models for agents, predicting future states based on current conditions and actions, allowing for internal simulation and decision-making [5]. - The engineering perspective defined world models as a combination of three capabilities: compressing high-dimensional perception into usable representations, predicting future states over time, and utilizing predictions for planning and decision-making [6]. - By 2024, the understanding of world models expanded to encompass general world evolution modeling, with a trend from language generation to image generation, and ultimately to 3D and world generation [6]. - The boundaries of the world model concept have become more ambiguous, with ongoing debates about the nature of representations, the incorporation of physical laws, and the organization of input relationships [6]. Group 2: Industry Layout and Trends - Major companies are investing in world models, questioning whether they are enhancing their "data engines" or building new frameworks for "spatiotemporal cognition" [3]. - In February 2024, OpenAI referred to the video generation model Sora as "world simulators," emphasizing their ability to learn the three-dimensional structure and physical laws of the real world [6]. - Concurrently, LeCun introduced V-JEPA, which focuses on predicting masked video segments in abstract representation space, allowing for higher training efficiency by discarding unpredictable information [6]. - The current discourse has shifted from whether to develop world models to how to model them, with debates on whether to abstract from pixel levels or to directly operate in abstract spaces [7]. - There is a recognition that existing approaches may only capture partial physical laws, indicating a need for representations of isolated objects and a priori laws of change across space and time to achieve a coherent world model [7]. Group 3: Definition and Ambiguity of World Models - By 2025, world models are positioned alongside LLMs, with companies like Google DeepMind, Meta, and Nvidia shifting focus from pure LLMs to world models, aiming for "Physical AI + superintelligence" due to stagnation in LLM advancements [8]. - The distinction between world models and existing generative AI lies in the former's goal to construct internal representations of environments that include physical, temporal, and spatial dimensions for planning and decision-making [9]. - The term "world model" has become ambiguous, referring to latent states within systems, game-like simulators for training agents, or any content pipeline capable of generating navigable 3D scenes [9]. - An analysis from Entropy Town in November 2025 categorized world models into three technical routes: interface, simulator, and cognitive framework, highlighting the ongoing ambiguity in the field [9].

RT Ezra Feilden (@ezrafeilden)Very happy to announce we have also used our @Nvidia H100 on Starcloud-1 to run inference with @GoogleDeepMind's Gemma model - the open source version of Gemini.These are Gemma's first words in space.<< Greetings, Earthlings! Or, as I prefer to think of you – a fascinating collection of blue and green. Let’s see what wonders this view of your world holds. I’m Gemma, and I’m here to observe, analyze, and perhaps, occasionally offer a slightly unsettlingly insightful commentary. ...

[applause] Seems like I'm not alone in wishing for a time machine. This is a sketch of my family. About a decade back, my father was diagnosed with Parkinson's disease.I saw him battle the disease for years and ultimately it took him away for us. And in those moments, I wish for a time machine more than anything else. Not to change the past, but to bring forward the future of medicine.So that we could give him all the incredible new cures that we are discovering today and the continuous care of a worldclass ...

Core Insights - Investors are eagerly searching for the next unicorn with a valuation exceeding $10 billion, with Mercor being a standout example that has redefined data infrastructure in the LLM era [1] - Mercor's valuation has surged to over $10 billion in its latest funding round, five times its pre-transformation valuation, highlighting its innovative approach to integrating high-level talent, specialized computing power, and data assets [1] - The emergence of Lightwheel as a potential competitor in the data infrastructure space indicates a shift towards a new paradigm in AI development, focusing on simulation data as a critical resource for world models and embodied intelligence [2][12] Group 1: The Evolution of Data Infrastructure - Silicon Valley has seen a pattern where each AI technology paradigm shift creates significant opportunities in the data layer, as evidenced by the transition from computer vision to large language models [2] - The current AI revolution driven by large language models emphasizes that while the model layer determines capability limits, the data layer is essential for breakthroughs [3] - Scale AI's success in the previous AI paradigm was due to its focus on providing standardized data annotation services, which addressed the critical bottleneck of data availability in the autonomous driving sector [4] Group 2: The Role of Mercor and Lightwheel - Mercor has effectively identified a niche market by creating a platform that connects global AI researchers and domain experts, managing over 30,000 contract workers across various fields [7] - The company has transitioned from a talent platform to a smart productivity infrastructure, embedding high-level human intelligence into the AI value cycle, thus becoming a key player in AI infrastructure [7] - Lightwheel is emerging as a significant player in the data infrastructure landscape, focusing on simulation data and aiming to become a foundational platform for world models and embodied intelligence [12][13] Group 3: Future of Data Platforms - The next generation of data platforms will need to support the construction of world models, shifting from serving language models to providing the foundational data for cognitive understanding of the physical world [10] - Lightwheel's approach to data production emphasizes automation and high-fidelity simulation, moving away from traditional human-centric data collection methods [11] - The demand for high-quality, reusable data is driving Lightwheel's evolution into a central hub for data supply in the world model ecosystem, creating a self-reinforcing data flywheel [19][20]

RT Philipp Schmid (@_philschmid)we now have a @GoogleDeepMind Luma page for events where the team is going to https://t.co/jSnyucNWjZ https://t.co/EHuhp5KeHm ...

Group 1: Market Overview - The Shanghai Composite Index closed at 3914 points, with a daily increase of 0.65% and a monthly increase of 2.01% [1] - The Shenzhen Composite Index closed at 2479 points, with a daily increase of 1.02% and a monthly increase of 3.68% [1] - The large-cap index showed a 1.07% increase yesterday but a decline of 1.25% over the past month, while the mid-cap index increased by 1.23% yesterday but declined by 3.23% over the past month [1] Group 2: Industry Performance - The professional chain industry saw a daily increase of 4.36%, while the industrial metals sector increased by 4.12% with a significant 66.19% increase over the past six months [1] - The communication equipment sector increased by 3.3% yesterday and has seen a remarkable 120.4% increase over the past six months [1] - The aquaculture industry experienced a decline of 1.4% yesterday and a 1.25% decline over the past month [1] Group 3: AI and Internet Media Investment Strategy - The report emphasizes the ongoing expansion of AI capital expenditure (capex) in 2026, particularly focusing on the return on investment (ROI) from AI investments [2][11] - Key companies highlighted for investment include Alibaba, Baidu, and Kingsoft Cloud, with a focus on their AI capabilities and market positioning [2][11] - The report suggests that the commercialization of AI applications will become a priority, with significant growth expected in AI advertising and video tools [11] Group 4: Convertible Bonds Analysis - The weighted average remaining maturity of convertible bonds has decreased to approximately 2.53 years, with nearly 40% of convertible bonds having a remaining maturity of less than 2 years [3][12] - The report predicts that by the end of 2026, the weighted average remaining maturity of convertible bonds will further decrease to around 2.0 years, indicating a "super short duration" market [3][12] - The analysis indicates that as the remaining maturity shortens, the valuation of convertible bonds will likely decline, particularly for those with less than 2 years remaining [12][13] Group 5: Hengbo Co., Ltd. (301225) Analysis - Hengbo Co., Ltd. is positioned as a leading supplier in the intake system market, with projected net profits of 152 million, 178 million, and 207 million yuan for 2025-2027, reflecting growth rates of 16.2%, 16.8%, and 16.2% respectively [3][14] - The company is expanding its business into new areas such as thermal management systems and PEEK materials, aiming to enhance its market presence and profitability [3][14] - The report assigns a "buy" rating to Hengbo Co., Ltd., with a target market value of 12.6 billion yuan, indicating a potential upside of 22% [3][14]

Great article from @jeremyakahn in Fortune on the huge impact of AlphaFold on biological and biomedical research.Jeremy Kahn (@jeremyakahn):Five years on, Google DeepMind’s AlphaFold shows why science may be AI’s killer app https://t.co/rt0XgSTGlo ...