Group 1: AI Models - Grok Code Fast 1 developed by xAI is highlighted as a significant model [3] - LongCat-Flash introduced by Meituan showcases advancements in AI modeling [3] - Claude's performance degradation rollback indicates challenges in maintaining model efficiency [3] - Shanghai AI Laboratory's Shusheng·Wanshang 3.5 represents a new iteration in AI models [3] - Kimi K2-0905 from Moonlight Dark Side is noted for its innovative features [3] - Kuaishou's new multimodal model reflects the trend towards integrating various data types [3] Group 2: AI Applications - Meta's third-party AI collaboration emphasizes the importance of partnerships in AI development [3] - OpenAI's GPT-realtime application showcases real-time AI capabilities [3] - Claude's user data utilization raises discussions on data privacy and usage [3] - Tencent's Hunyuan-MT-7B highlights advancements in machine translation [3] - Step-Audio 2 mini from Jiyue Xingchen represents innovation in audio processing [3] - Hyodol's AI doll for elderly users indicates a growing market for AI in healthcare [3] - Multi-department and platform AI content identification reflects regulatory trends [3] - Tsinghua's embodied reinforcement framework shows advancements in AI learning [3] - Google's "Detailed Webpage" feature enhances user experience through AI [3] - Tencent's 3D world model indicates a shift towards immersive AI applications [3] - Runway's cross-domain robots illustrate the versatility of AI in various fields [3] Group 3: Technology and Research - Tsinghua's robot ping pong showcases the intersection of robotics and AI [5] - UCLA's AI brain-machine interface represents cutting-edge research in human-computer interaction [5] - The machine wolf project from 93rd Military Parade indicates military applications of AI [5] - RoboScience's RoboMirage simulation reflects advancements in AI-driven simulations [5] - Tesla's "Golden Pillar" project highlights the integration of AI in automotive technology [5] - Shanghai AI Laboratory's research on AI evolution in scientific fields indicates ongoing innovation [5] Group 4: Capital and Investment - OpenAI's acquisition of Statsig signifies strategic growth through mergers [5] - Anthropic's $13 billion financing round indicates strong investor confidence in AI [5] - OpenAI's recruitment of the Alex team reflects competitive talent acquisition in the industry [5] Group 5: Events and Trends - The Werewolf game battle involving GPT-5 indicates the application of AI in entertainment [5] - xAI's engineer defection raises concerns about talent retention in AI companies [5] - Meta's new executive departure highlights challenges in leadership stability [5] - Salesforce's 4,000 layoffs reflect broader trends in workforce adjustments within tech [5] Group 6: Perspectives and Insights - a16z's insights on AI hardware entry points suggest strategic investment opportunities [5] - DeepSeek's details on V3/R1 training provide valuable information for AI model development [5] - Tesla's grand blueprint outlines ambitious future plans for AI integration [5] - The use of AI by students in U.S. universities indicates a growing acceptance of AI in education [5] - OpenAI experts' strategies on AI PM reflect evolving management practices in tech [5] - OpenAI's leadership guide offers insights into effective management in AI-driven environments [5]

Core Viewpoint - The article explores the complex phenomenon of consciousness from various interdisciplinary perspectives, aiming to connect different theories and establish a computational framework for understanding consciousness and its implications for artificial intelligence [2][9]. Group 1: Introduction and Definition of Consciousness - Consciousness is defined as a multifaceted concept involving awareness, wakefulness, and subjective experience, with distinctions made between these related but different concepts [7][16]. - The article emphasizes the importance and difficulty of understanding human consciousness, aiming to engage various research communities in this exploration [7][8]. Group 2: Theoretical Frameworks - The article outlines several influential theories of consciousness, including Information Integration Theory (IIT), Orchestrated Objective Reduction Theory (Orch OR), Global Workspace Theory (GWT), High-Order Theories (HOT), Attention Schema Theory (AST), and Conscious Turing Machine (CTM) [8][38]. - IIT posits that consciousness corresponds to the ability of a system to integrate information, with a focus on the causal power of the system [42][46]. Group 3: Measurement of Consciousness - Recent research has developed effective methods for measuring human consciousness, including indices based on electrical signals and behavioral assessments [18][19]. - The Perturbational Complexity Index (PCI) is highlighted as a significant measure for distinguishing between conscious and unconscious states [19][20]. Group 4: Consciousness and Intelligence - The article discusses the distinction between consciousness and intelligence, noting that consciousness is often considered more mysterious and difficult to measure than intelligence [22][23]. - The relationship between consciousness and free will is explored, with ongoing debates about the existence of true free will and its connection to consciousness [28][29]. Group 5: Sleep and Consciousness - The article examines consciousness during sleep, noting that different sleep stages (REM and NREM) exhibit varying levels of awareness and perception [35][36]. - Information Integration Theory suggests that consciousness diminishes during deep sleep due to reduced integration of brain activity [36][37]. Group 6: Biological Evidence and Theories - The article discusses biological evidence supporting the theories of consciousness, particularly the role of the brain's cortical areas in information integration [49]. - The Orch OR theory is presented as a hypothesis linking consciousness to quantum processes, suggesting that true randomness may be necessary for free will [65].

Group 1 - OpenAI has acquired the Alex team, known for its powerful coding assistant plugin for Xcode, indicating its intention to expand influence in the Apple app development ecosystem [1] - Apple plans to launch an AI search engine called "World Knowledge Answers" in Spring 2026, competing directly with ChatGPT and Perplexity [2] - Apple is facing a talent drain in its AI division, having lost 10 AI researchers, including key personnel, to Meta in recent weeks [2] Group 2 - The new Kimi K2-0905 model from Moonlight has enhanced programming capabilities and supports 256K context length, doubling the previous version's capacity [3] - Kimi K2-0905 maintains state-of-the-art performance in creative writing and improves compatibility with Claude Code [3] Group 3 - Kuaishou has open-sourced its 8 billion parameter multimodal model Keye-VL-1.5, achieving state-of-the-art results in video understanding benchmarks [4] - Keye-VL-1.5 can process several minutes of video content in under 10 seconds and introduces innovative training strategies for video recommendation and content review [4] Group 4 - OpenAI has introduced the Projects feature to the free version of ChatGPT, allowing users to manage up to 5 files and customize project settings [5][6] - This feature enhances the efficiency of ChatGPT by enabling centralized management of related content [5] Group 5 - Salesforce has announced the layoff of approximately 4,000 customer support positions, attributing this to the efficiency gains from its AI system, Agentforce [7] - The CEO stated that AI now handles up to 50% of internal workloads, while the company plans to hire 1,000 to 2,000 sales personnel to promote AI's value [7] Group 6 - A comprehensive review of scientific large language models (Sci-LLMs) has been published, detailing over 600 datasets and models, and highlighting four paradigm shifts from 2018 to 2025 [9] - The review emphasizes the importance of data quality and proposes a dynamic assessment model for scientific knowledge [9] Group 7 - OpenAI released a white paper outlining leadership strategies for maintaining a competitive edge in the AI era, noting that early adopters of AI see revenue growth 1.5 times faster than their peers [10] - The report suggests five core principles for organizations to follow in their AI strategy and implementation [10]

Core Viewpoint - The article discusses the concept of "bubble community" as a complex and dynamic structure in the digital age, emphasizing the coexistence of isolation and connection among individual information bubbles, challenging the traditional narrative of "information cocoons" [31][22]. Group 1: Conceptual Framework - The terms "information cocoon," "filter bubble," and "echo chamber" attempt to describe a shared experiential space, which can be categorized into three forms: bubbles, spheres, and foams, as proposed by philosopher Peter Sloterdijk [3][5]. - Bubbles represent the smallest unit of coexistence, symbolizing intimate relationships, while spheres denote larger, closed communities that provide safety from external threats [3][5][6]. - Foams consist of interconnected bubbles, representing an open yet fragile social structure, where individual bubbles maintain their independence while influencing one another [6][8]. Group 2: Algorithmic Influence - Algorithms create a "pampered space" for users by filtering out uncomfortable information and reinforcing cognitive biases, leading to a "cognitive immune space" [10][12]. - The filtering mechanism passively constructs boundaries, while the "adhesion mechanism" actively strengthens these boundaries through user interactions, such as likes and shares [11][12]. - This results in a parasitic structure where users become laborers in data capitalism, trading their data for a comfortable cognitive environment [12][13]. Group 3: Challenges of Digital Interaction - The article highlights the shift from emotional resonance to adversarial stimuli as the glue that binds groups together, leading to polarization and a lack of diverse viewpoints [13][15]. - Individual fluidity is constrained within algorithmic pampered spaces, where users appear to have freedom but are actually confined to predetermined cognitive frameworks [14][15]. - The self-consuming cycle of information within these bubbles leads to a gradual loss of vitality and diversity, as members become increasingly homogeneous in their views [15][16]. Group 4: Cognitive Navigation - The concept of "cognitive cocoon" is introduced, emphasizing that the real challenge lies in cognitive rigidity rather than mere information isolation [19][20]. - Individuals often reject opposing viewpoints due to confirmation bias and the fear of cognitive dissonance, reinforcing their existing beliefs [19][20]. - The article argues that breaking free from cognitive cocoons requires more than just exposure to diverse information; it necessitates a shift in mindset and the ability to engage with differing perspectives [16][19]. Group 5: Optimizing Bubble Communities - The article proposes three strategies for optimizing bubble communities: algorithmic intervention, sphere re-gasification, and social engineering [24][25][27]. - Algorithmic intervention involves injecting "heterogeneous bacteria" into recommendation systems to enhance cognitive diversity [24]. - Sphere re-gasification aims to make rigid boundaries more permeable, facilitating interaction between different bubbles [25]. - Social engineering emphasizes the need for a collective social contract among users, platforms, and governments to foster a healthier information ecosystem [27][28].

生成式AI 一、 OpenAI斥资11亿美金，收购软件开发平台公司Statsig 1. OpenAI以11亿美元收购软件实验和分析平台Statsig，并任命创始人Vijaye Raji为OpenAI应用部门新CTO； 2. Statsig帮助软件团队判断代码是否该上线及效果评估，这次收购显示OpenAI战略重心从纯底层模型研发转向打造 数据驱动的终端用户产品； 3. Vijaye Raji曾在微软工作十年，后在Meta担任高管十年，2021年创立Statsig，期间表现出卓越的编程能力和领 导才能，将直接向OpenAI应用CEO Fidji Simo汇报。 https://mp.weixin.qq.com/s/_eGHvABP5GK2FfCEl1jlfw 二、 又一万亿AI独角兽诞生，Anthropic完成130亿美元融资 1. Anthropic宣布完成130亿美元F轮融资，投后估值达1830亿美元，成为仅次于OpenAI、字节跳动的全球第三大AI 独角兽； 1. 谷歌发布nano banana(Gemini 2.5 Flash Image)官方Prompt模板，覆盖写实摄影、贴纸、文本渲染、商业摄 影、留 ...

Group 1 - Google Gemini API has launched the "URL Context" feature, allowing deep access and processing of content from URLs, including web pages, PDFs, and images [1] - The feature employs a two-step retrieval process, capable of parsing tables, text structures, and footnotes in PDFs, with a capacity limit of 34MB and a maximum of 20 URLs per request [1] - URL Context is seen as a significant advancement, eliminating the need for cumbersome processes like extraction and storage, exemplified by its ability to accurately extract data from a 50-page Tesla PDF [1] Group 2 - Tencent has released the latest member of its Hunyuan 3D world model series, HunyuanWorld-Voyager, which is the first model to support native 3D reconstruction for long-distance roaming [2] - Hunyuan Voyager breaks traditional video generation limitations, enabling the creation of consistent roaming scenes and direct export of videos in 3D format, highly compatible with Hunyuan World Model 1.0 [2] - The model ranked first in comprehensive capability in the WorldScore benchmark test released by Stanford University's Fei-Fei Li team, supporting various applications like video scene reconstruction and 3D object texture generation [2] Group 3 - Runway, a visual generation AI company, has secured over $500 million in funding from investors including Nvidia and Google, achieving a valuation of $3 billion as it enters the robotics field [3] - Runway's AI world model provides training simulations for robotics and autonomous vehicle companies, creating efficient and cost-effective virtual testing environments [3] - Compared to real-world training, Runway's model allows users to control specific variable tests more precisely, particularly useful for evaluating different operations in the same environment [3] Group 4 - Tencent Youtu Lab has open-sourced the Youtu-Agent framework, which features user-friendly, low-cost, flexible architecture, and automatic agent generation [4] - The framework achieved a state-of-the-art accuracy of 71.47% on the WebWalkerQA benchmark using DeepSeek-V3.1, and 72.8% on the GAIA text subset, without requiring closed-source models [4] - It follows the DITA principle and provides four typical application cases: local file management, data analysis, paper analysis, and broad reviews, supporting one-click configuration and testing [4] Group 5 - The flowith team has launched a new parallel world game, flolife.me, which is an AI life simulator allowing players to create characters and have AI take over their life simulation [5][6] - The game process is straightforward: players input character details and attributes, and the system generates a complete life line with branching options [6] - Flolife generates various possibilities for key life events, showcasing bizarre stories and allowing users to select four highlight moments to create shareable posters [6] Group 6 - The Aivilization project from the Hong Kong University of Science and Technology allows users to create custom AI characters, setting MBTI personalities and goals, and observing their growth in a virtual town [7] - The game's evaluation system is singular, ranking players solely by money, leading to strategies that optimize for "dehumanization" by neglecting rest for profit [7] - Top players discovered that mining for initial funds and upgrading houses to manufacture chips can yield a passive income of 67,680 coins daily, far exceeding other life activities [7] Group 7 - The GLM-4.5 model from Zhipu AI has surpassed Claude Opus 4.1 in the Berkeley tool invocation ranking, with operational costs only 1.4% of its competitor [8] - This model utilizes a MoE architecture and performs strongly across six development areas and 52 practical programming tasks in the CC-Bench evaluation system, particularly in task completion and tool invocation reliability [8] - GLM-4.5 is three times faster than Opus 4.1 and five times faster than GPT-5, integrating with several mainstream programming tools at a cost of only 1/7 of Claude's price [8] Group 8 - A UCLA team has developed an AI-assisted non-invasive brain-machine interface system that significantly enhances the performance of paralyzed participants in controlling computer cursors, improving accuracy nearly fourfold [9] - The system operates in an "AI co-pilot" mode, dividing tasks between humans and AI, where humans focus on decision-making while AI predicts and assists in execution [9] - Experiments showed that participants using the AI co-pilot system reduced cursor control time from 4.15 seconds to 0.05 seconds, with correct placement rates for robotic arms increasing from 0 to 93% [9] Group 9 - Elon Musk has released "Master Plan 4," stating that 80% of Tesla's future value will come from the Optimus robot, emphasizing the integration of AI into the physical world [10][11] - The plan outlines five core principles: unlimited growth, innovation eliminating constraints, technology solving real problems, automation benefiting humanity, and broader accessibility leading to greater growth [10] - Compared to previous plans, Master Plan 4 places greater emphasis on AI as a core driving force, with Musk viewing cars as a specific instance of robots within a broader ecosystem [11] Group 10 - A survey of 1,000 students in the U.S. revealed that 85% use AI in their studies, primarily for brainstorming (55%), Q&A (50%), and exam preparation (46%), rather than for laziness [12] - 97% of students believe institutions should proactively address academic integrity challenges posed by AI, with 53% advocating for education on responsible AI use rather than restrictions [12] - Among AI users, 55% feel AI has mixed effects on learning and critical thinking, with 23% believing it enhances the value of higher education, while only 18% express increased skepticism about university value [12]

Core Viewpoint - The article discusses the transition from "Internet+" to "Artificial Intelligence+" as a new phase in technological integration, emphasizing the transformative potential of AI in reshaping industries and societal operations [5]. Group 1: Differences Between "Artificial Intelligence+" and "Internet+" - The technological stage differs, with "Internet+" being based on mature digital technologies while "Artificial Intelligence+" is characterized by rapid iteration and uncertainty in technology and applications [7]. - The value creation mechanism varies; "Internet+" enhances connectivity, while "Artificial Intelligence+" focuses on computational enhancement, improving productivity at each node and expanding the network's value [10]. - The diffusion paths are distinct; "Internet+" follows a consumer-to-producer model, while "Artificial Intelligence+" is more producer-focused, requiring deep integration into business processes before reaching consumers [12]. Group 2: Economic Impact of AI - AI's productivity effects are expected to grow exponentially, with predictions that AI could contribute to a 15% increase in global economic growth over the next decade [11]. - The rapid evolution of AI capabilities, with task completion abilities doubling approximately every seven months, indicates a significant potential for economic value creation [11]. Group 3: Practical Exploration of "Artificial Intelligence+" - Companies should prioritize high-value AI use cases that are data-rich and core to their business, as demonstrated by Pfizer's use of AI to enhance drug development efficiency [17]. - The engineering of AI systems is crucial, with companies needing to adapt general models to specific business needs through techniques like prompt engineering and retrieval-augmented generation [18]. - Building AI datasets should focus on business needs rather than data collection for its own sake, ensuring that data strategies are integrated throughout the AI application lifecycle [19]. Group 4: Recommendations for Promoting "Artificial Intelligence+" - A top-level design is necessary to create an innovative environment for "Artificial Intelligence+", similar to the strategic guidance that supported "Internet+" [22]. - Encouraging a diverse range of developers and startups in AI applications can foster innovation and investment in the sector [23]. - Establishing a comprehensive data element market and promoting open industry application scenarios can enhance the sustainable development of AI applications [25].

Group 1 - Meta and Scale AI partnership has deteriorated, with Ruben Mayer, a high-ranking executive who joined Meta from Scale AI, leaving the company just two months after the collaboration began [1] - Meta's internal researchers have complained about the low data quality from Scale AI, prompting Meta to shift its focus to competitors Mercor and Surge [1] - Following the loss of Meta's support, Scale AI has also lost major clients like OpenAI and Google, leading to significant layoffs [1] Group 2 - Users reported a significant performance decline in Claude Opus 4.1 during the daytime, particularly between 10-11 AM, with frequent errors in document processing [2] - Analysis suggests that the performance drop may be due to Anthropic's use of 1.58-bit quantization during the day, which resulted in the loss of critical information [2] - Anthropic has acknowledged the issue as a problem with the inference stack and has rolled back to previous versions 4.1 and 4.0 to restore quality [2] Group 3 - Tencent has open-sourced the 7B parameter translation model Hunyuan-MT-7B, which supports 33 languages and has achieved first place in 30 out of 31 languages in the WMT2025 competition [3] - The company also released the first translation integration model, Hunyuan-MT-Chimera-7B, which generates superior translations based on original text and multiple model outputs [3] - The model utilizes AngelSlim compression for FP8 quantization, improving inference performance by 30% and is integrated into various Tencent services [3] Group 4 - Jieyue Star has launched the end-to-end speech model Step-Audio 2 mini, which integrates speech understanding, audio reasoning, and generation, along with native Tool Calling capabilities [4] - The model has excelled in multiple benchmark tests, achieving an MMAU score of 73.2, ranking first among open-source end-to-end speech models [4] - It employs a true end-to-end multimodal architecture, incorporating chain reasoning and reinforcement learning for enhanced understanding of emotions, tones, and non-verbal signals [4] Group 5 - Shanghai AI Laboratory has released the Shusheng·Wanxiang InternVL3.5 series models, featuring nine sizes with parameters ranging from 1 billion to 241 billion, enhancing general capabilities, reasoning abilities, and deployment efficiency [5] - The flagship model InternVL3.5-241B-A28B surpasses GPT-5 in several benchmarks, achieving a score of 77.7 in MMMU, the highest for open-source models [5] - Innovations include dynamic visual resolution routing and a decoupled deployment framework, reducing inference latency from 369ms to 91ms, enhancing core capabilities [6] Group 6 - The South Korean government has distributed AI dolls developed by startup Hyodol to tens of thousands of elderly individuals living alone, providing companionship and health monitoring [7] - The dolls feature a ChatGPT-based dialogue system and sensors to detect movements, with the ability to alert caregivers in emergencies [7] - Over 12,000 Hyodol dolls are currently in use, priced at approximately 8,160 RMB each, significantly lower than the cost of caregiving staff, addressing the shortage of nursing personnel in South Korea [7] Group 7 - As of September 1, the "Identification Method for AI-Generated Synthetic Content" has been implemented, requiring AI-generated content to include identity tags [8] - Providers of synthetic content must add explicit and implicit identifiers, while platforms must verify metadata and provide clear indications [8] - Major platforms like Tencent, Douyin, Kuaishou, Bilibili, and DeepSeek have announced detailed rules and functionalities for adding identifiers to AI content, prohibiting users from deleting or altering these tags [8] Group 8 - Tsinghua University and partners have released RLinf, the first large-scale reinforcement learning framework for embodied intelligence, featuring a new hybrid execution model [9] - The framework achieves over 120% system acceleration in training scenarios for embodied intelligence [9] - It integrates Megatron+SGLang/vLLM and FSDP+HuggingFace backends, designed for different training needs, and includes adaptive communication libraries and automatic scheduling modules [9] Group 9 - DeepSeek has published an official announcement in response to the new regulations, committing to label AI-generated content and warning users against modifications [10] - The company has disclosed training details for its models, including a scale of 685 billion parameters and the pre-training and optimization processes [10] - DeepSeek has outlined its data governance system, employing filters to eliminate harmful content while ensuring user rights to information, choice, and control, acknowledging the ongoing challenge of "hallucinations" in models [10]

Core Viewpoints - The current AI models exhibit a tendency to provide answers regardless of accuracy, reflecting their nascent technological stage [2] - The rise of AI is leading to a decline in individual cognitive independence and an increased reliance on collective intelligence, effectively transferring cognitive burdens to external models [5][6] - The future may redefine life itself, with machines emerging as a new species, blurring the lines between pure humans and cyborgs [10][11] Group 1: Impact on Individual and Collective Intelligence - AI is causing a decrease in individual knowledge independence while increasing dependence on collective wisdom, a trend that has evolved from the internet and social networks to current AI models [5] - The ease of accessing vast amounts of information through AI leads to a decline in personal confidence in decision-making, as individuals struggle to determine the appropriateness of various analytical perspectives [6] - The dual nature of AI's impact should not be simplistically categorized as either "dumbing down" or "enlightening," as both effects can coexist and transform over time [6] Group 2: Future Economic and Social Structures - The future manufacturing landscape is expected to become automated and public-oriented, with production, consumption, and distribution occurring concurrently rather than sequentially [7] - Economic models will shift from being transaction-centered to focusing on individual intentions, organizing around personal interests and genuine needs [7][15] - The emergence of a "machine world" will redefine human production, organization, and consumption, leading to a potential overhaul of traditional human reproductive methods through technologies like artificial wombs [11] Group 3: Human-Machine Relationship - Discussions about human-machine relationships must adopt a long-term perspective, recognizing the need to redefine concepts of life and existence in light of advancements in biotechnology and AI [9][10] - The evolution from "human consensus" to "human-machine consensus" is crucial, requiring acceptance of machines potentially possessing free will and the need for humans to adapt to this new reality [11][12] Group 4: New Economic Logic and Cultural Integration - The transition to a new economic logic will be driven by the realization that inequality stems from mismatches rather than scarcity, leading to a focus on real-time distribution based on individual intentions [15] - The integration of Eastern and Western cultural wisdom is essential to address the limitations of current economic theories and to foster a revival of public spirit in a highly interconnected world [14][16]

Group 1: Generative AI Developments - xAI launched Grok Code Fast 1, which is five times faster than GPT-5 and ranks among the top five coding models globally, focusing on real programming tasks and supporting multiple languages [1] - Meta is seeking partnerships with OpenAI or Google to enhance its AI capabilities, as its internal flagship model Llama 5 is progressing slowly, reflecting a sense of urgency in the AI race [2] - OpenAI introduced GPT-realtime, featuring advanced voice generation and improved accuracy, with a new API that lowers costs and enhances application flexibility [3] Group 2: Data Privacy and User Engagement - Claude updated its privacy policy to allow user data collection for model training, which has drawn criticism for contradicting its earlier stance on data security [4] Group 3: Model Performance and Innovations - Meituan open-sourced the LongCat-Flash model with 560 billion parameters, achieving high efficiency and speed, and performing well in various benchmarks [5] - GPT-5 demonstrated superior social reasoning and manipulation skills in a series of games, achieving a 96.7% win rate, highlighting its dominance in social intelligence [6][7] Group 4: Talent Movement and Legal Issues - xAI's founding engineer was accused of stealing core code and moving to OpenAI after cashing out approximately $7 million in stock, leading to a lawsuit over trade secrets [8] Group 5: Robotics and AI Interaction - Tsinghua University's team developed a framework allowing a robot to play table tennis with high accuracy, showcasing advancements in dynamic interaction capabilities [9] Group 6: AI Hardware Insights - a16z's Bryan Kim emphasized the need for hardware to facilitate more natural interactions with AI, identifying key factors for success in AI hardware applications [10]