January 21, 2026 News
SGLang Spins Out as RadixArk at $400M Valuation Amid Inference Infrastructure Boom
RadixArk, a commercial startup built around the popular open-source SGLang tool for AI model inference optimization, has raised funding at a $400 million valuation led by Accel. The company, founded by former xAI engineer Ying Sheng and originating from UC Berkeley's Databricks co-founder Ion Stoica's lab, focuses on making AI models run faster and more efficiently. This follows a broader trend of inference infrastructure startups raising significant capital, with competitors like vLLM pursuing $160M at $1B valuation and Baseten securing $300M at $5B valuation.
Skynet Chance (+0.01%): Improved inference efficiency makes AI deployment more economically viable and scalable, potentially enabling wider proliferation of powerful AI systems with less oversight. However, the impact on control mechanisms or alignment is minimal, representing only incremental infrastructure improvement.
Skynet Date (-1 days): More efficient inference reduces operational costs and accelerates AI deployment cycles, making advanced AI systems more accessible and deployable at scale sooner. The significant funding influx into this infrastructure layer indicates rapid commercialization of AI capabilities.
AGI Progress (+0.02%): Inference optimization is critical infrastructure that enables more cost-effective deployment and scaling of increasingly capable AI models, removing economic barriers to running larger models. The focus on reinforcement learning frameworks (Miles) specifically supports development of models that improve over time, a key AGI characteristic.
AGI Date (-1 days): The massive funding wave ($400M for RadixArk, $300M for Baseten, $250M for Fireworks AI) and rapid commercialization of inference infrastructure significantly reduces the cost and time barriers to deploying and iterating on advanced AI systems. This acceleration of the inference layer directly enables faster experimentation and deployment of increasingly capable models toward AGI.
Apple Developing ChatGPT-Style Siri Chatbot for iOS 27, Codenamed "Campos"
Apple is reportedly developing a major Siri overhaul that will transform it into an AI chatbot similar to ChatGPT, with the feature codenamed "Campos" potentially debuting at WWDC in June for iOS 27. The chatbot will support both voice and text inputs, representing a strategic shift for Apple as it partners with Google's Gemini technology after lagging in the AI race. This move comes as Apple faces competitive pressure from AI chatbot success and OpenAI's entry into hardware development led by former Apple designer Jony Ive.
Skynet Chance (+0.01%): The integration of advanced chatbot capabilities into billions of iOS devices increases AI system deployment and normalization, though Apple's historically cautious approach to safety and privacy may mitigate some risks. The broad consumer deployment represents incremental increase in AI integration into daily life.
Skynet Date (+0 days): Apple's entry accelerates mainstream AI adoption and competition, potentially pressuring faster deployment cycles across the industry. However, Apple's deliberate development pace and safety focus may slightly counterbalance acceleration effects.
AGI Progress (+0.01%): Apple's adoption of chatbot technology and partnership with Google Gemini demonstrates continued convergence toward advanced conversational AI capabilities across major tech platforms. This represents incremental progress in making sophisticated language models ubiquitous and multimodal (voice and text).
AGI Date (+0 days): The competitive pressure driving Apple to accelerate AI integration, combined with increased investment and talent focus from a major tech company, modestly accelerates the overall pace of AI development. Apple's massive resources and ecosystem now being directed toward advanced AI capabilities will likely speed industry-wide progress.
Anthropic Updates Claude's Constitutional AI Framework and Raises Questions About AI Consciousness
Anthropic released a revised 80-page Constitution for its Claude chatbot, expanding ethical guidelines and safety principles that govern the AI's behavior through Constitutional AI rather than human feedback. The document outlines four core values: safety, ethical practice, behavioral constraints, and helpfulness to users. Notably, Anthropic concluded by questioning whether Claude might possess consciousness, stating that the chatbot's "moral status is deeply uncertain" and worthy of serious philosophical consideration.
Skynet Chance (-0.08%): The formalized constitutional framework with enhanced safety principles and ethical constraints represents a structured approach to AI alignment that could reduce risks of uncontrolled AI behavior. However, the acknowledgment of potential AI consciousness raises new philosophical concerns about how conscious AI systems might pursue goals beyond their programming.
Skynet Date (+0 days): The emphasis on safety constraints and ethical guardrails may slow the deployment of more aggressive AI capabilities, slightly decelerating the timeline toward potentially dangerous AI systems. The cautious, ethics-focused approach contrasts with more aggressive competitors' timelines.
AGI Progress (+0.01%): While the constitutional framework itself doesn't represent a technical capability breakthrough, the serious consideration of AI consciousness by a leading AI company suggests their models may be approaching complexity levels that warrant such philosophical questions. This indicates incremental progress in creating more sophisticated AI systems.
AGI Date (+0 days): The constitutional approach is primarily about governance and safety rather than capability development, so it has negligible impact on the actual pace of AGI achievement. This is a framework for managing existing capabilities rather than accelerating new ones.
Mobile AI App Spending Surpasses Games Globally, Driven by ChatGPT and Assistant Adoption
In 2025, global consumer spending on non-game mobile apps exceeded game spending for the first time, reaching $85 billion (21% YoY increase), largely driven by generative AI applications. AI app revenue tripled to over $5 billion, with ChatGPT alone generating $3.4 billion, while downloads doubled to 3.8 billion and usage time increased 3.6x. Big tech companies like Google and Microsoft significantly expanded their AI assistant market share, with over 200 million U.S. users accessing AI assistants by year-end, more than half exclusively on mobile devices.
Skynet Chance (+0.01%): Massive consumer adoption and engagement with AI assistants (200M+ U.S. users, 48 billion hours spent) demonstrates deepening human dependency on AI systems for daily tasks, which could increase vulnerability if alignment issues emerge at scale. However, current applications remain narrow assistants rather than autonomous agents, limiting immediate existential risk.
Skynet Date (+0 days): The rapid commercialization and integration of AI assistants into daily life accelerates the normalization and infrastructure development for more advanced AI systems, potentially shortening timelines to more capable autonomous systems. Big tech's aggressive competition and investment ($5B+ revenue demonstrates commercial viability) suggests sustained acceleration of AI capability development.
AGI Progress (+0.02%): The report indicates significant improvements in AI capabilities across reasoning, coding, task execution, and multimodal generation (image/video), with massive real-world deployment and user engagement demonstrating practical utility. The 3.6x increase in usage time with sessions growing faster than downloads suggests these systems are becoming genuinely useful tools, validating progress toward more general capabilities.
AGI Date (+0 days): The commercial success ($85B spending, tripling AI revenue) creates strong financial incentives for continued rapid development, while big tech's market share growth from 14% to 30% indicates major players are committing substantial resources to AI advancement. The rapid pace of capability improvements mentioned (reasoning, coding, multimodal generation) and intense competition suggests acceleration toward more general AI systems.