January 27, 2026 News
Anthropic Doubles Funding Target to $20B, Valuation Soars to $350B
Anthropic is raising its venture capital funding target from $10 billion to $20 billion due to strong investor demand, which would value the AI company at $350 billion. The company, known for its Claude AI assistant and Claude Code products, expects the funding round to close soon with participation from major investors including Sequoia Capital, Singapore's sovereign wealth fund, and Coatue. This follows a previous $13 billion raise in September that valued the company at $183 billion, and comes as Anthropic prepares for a potential IPO later this year.
Skynet Chance (+0.04%): Massive capital influx enables Anthropic to accelerate AI capability development with fewer resource constraints, potentially advancing powerful AI systems faster than safety protocols can mature. However, Anthropic's stated focus on AI safety partially mitigates this concern.
Skynet Date (-1 days): The unprecedented $20 billion funding and $350 billion valuation reflect accelerating investment in frontier AI capabilities, likely speeding development timelines for increasingly powerful AI systems. This capital enables more aggressive scaling and research initiatives that could advance capabilities ahead of safety frameworks.
AGI Progress (+0.03%): The doubling of funding target to $20 billion and tripling of valuation to $350 billion demonstrates extraordinary market confidence in Anthropic's path toward advanced AI capabilities. This level of capital enables massive compute investments, talent acquisition, and research initiatives critical for AGI development.
AGI Date (-1 days): The unprecedented capital infusion significantly accelerates Anthropic's ability to scale compute infrastructure, hire top talent, and conduct extensive research, compressing the timeline for developing increasingly general AI capabilities. The competitive funding environment also intensifies the AI race among frontier labs.
OpenAI Releases Prism: AI-Powered Scientific Research Workspace Integrated with GPT-5.2
OpenAI has launched Prism, a free AI-enhanced workspace for scientific research that integrates GPT-5.2 to help researchers assess claims, revise writing, and search literature. The tool is designed to accelerate human scientific work similar to how AI coding assistants have transformed software engineering, with features including LaTeX integration, diagram assembly, and full research context awareness. OpenAI executives predict 2026 will be a breakthrough year for AI in science, following successful applications in mathematical proofs and statistical theory.
Skynet Chance (+0.01%): The tool emphasizes human-in-the-loop collaboration rather than autonomous AI research, maintaining human oversight and verification of scientific claims. This design choice suggests a measured approach to AI capabilities expansion, though any advancement in AI scientific reasoning does incrementally increase capability risks.
Skynet Date (+0 days): By accelerating scientific research broadly, including potentially AI safety research, the tool could modestly speed up overall AI development timelines. However, the human-supervised nature and focus on assisting rather than replacing researchers limits the acceleration effect.
AGI Progress (+0.02%): The integration of GPT-5.2 with scientific research workflows and demonstrations of AI proving mathematical theorems and statistical axioms represents meaningful progress in AI's ability to engage with complex formal reasoning. The tool's success in domains requiring rigorous logical reasoning indicates growing general intelligence capabilities.
AGI Date (+0 days): By creating infrastructure that accelerates scientific research including AI research itself, and by demonstrating GPT-5.2's ability to handle advanced mathematics and formal verification, this tool could meaningfully speed the pace toward AGI development. The comparison to how AI transformed software engineering in 2025 suggests similar productivity multipliers may apply to AI research workflows.
Moonshot AI Launches Multimodal Open-Source Model Kimi K2.5 with Advanced Coding Capabilities
China's Moonshot AI released Kimi K2.5, a new open-source multimodal model trained on 15 trillion tokens that processes text, images, and video. The model demonstrates competitive performance against proprietary models like GPT-5.2 and Gemini 3 Pro, particularly excelling in coding benchmarks and video understanding tasks. Moonshot also launched Kimi Code, an open-source coding tool that accepts multimodal inputs and integrates with popular development environments.
Skynet Chance (+0.01%): The release of a powerful open-source multimodal model with advanced agentic capabilities increases accessibility to sophisticated AI systems, potentially making it harder to maintain centralized safety controls. However, open-source models also enable broader safety research and scrutiny, providing modest offsetting benefits.
Skynet Date (+0 days): Open-sourcing competitive multimodal and agentic capabilities accelerates the diffusion of advanced AI technology globally, potentially shortening timelines for both beneficial applications and potential misuse scenarios. The model's strong performance in agent orchestration particularly suggests faster development of autonomous systems.
AGI Progress (+0.03%): The model demonstrates significant progress toward AGI-relevant capabilities including native multimodal understanding across text, images, and video, plus advanced coding and multi-agent orchestration at performance levels matching or exceeding leading proprietary systems. Training on 15 trillion tokens and achieving strong benchmark results across diverse tasks indicates meaningful advancement in general capability.
AGI Date (-1 days): The rapid development and open-source release of a competitive multimodal model by a well-funded Chinese startup demonstrates accelerating global competition and capability advancement in AI. The model's strong coding performance and agent orchestration capabilities, combined with increasing commercialization of coding tools reaching billion-dollar revenues, suggests faster-than-expected progress toward AGI-relevant capabilities.