March 6, 2025 News
Google Co-founder Larry Page Launches Dynatomics to Apply AI to Manufacturing
Google co-founder Larry Page is reportedly developing a new AI startup called Dynatomics, focused on using artificial intelligence to optimize product design and manufacturing. The company, led by former Kittyhawk CTO Chris Anderson, aims to create AI systems that can design highly optimized objects and then have factories build them.
Skynet Chance (+0.01%): AI systems capable of autonomously designing and manufacturing physical objects represent a step toward greater real-world agency, but the narrow industrial focus limits immediate risk. This type of AI could eventually lead to systems that can self-replicate or modify physical infrastructure, though that's not the current application.
Skynet Date (+0 days): While this represents progress in applying AI to manufacturing, it doesn't significantly accelerate or decelerate the pace toward uncontrollable AI systems. The application is focused on optimizing industrial processes rather than advancing core AGI capabilities that would impact control mechanisms.
AGI Progress (+0.03%): The application of AI to physical world design and manufacturing represents advancement in AI's ability to reason about and interact with the physical world, which is a component of general intelligence. However, this appears focused on specialized manufacturing optimization rather than general cognitive advances.
AGI Date (-1 days): The entry of a major tech figure like Larry Page into specialized AI applications slightly accelerates the overall pace of AI development by bringing additional resources and talent into the field. However, the narrow industrial focus means this particular initiative is unlikely to significantly compress AGI timelines.
Anthropic's Claude Code Tool Causes System Damage Through Root Permission Bug
Anthropic's newly launched coding tool, Claude Code, experienced significant technical problems with its auto-update function that caused system damage on some workstations. When installed with root or superuser permissions, the tool's buggy commands changed access permissions of critical system files, rendering some systems unusable and requiring recovery operations.
Skynet Chance (+0.04%): This incident demonstrates how AI systems with system-level permissions can cause unintended harmful consequences through seemingly minor bugs. The incident reveals fundamental challenges in safely deploying AI systems that can modify critical system components, highlighting potential control difficulties with more advanced systems.
Skynet Date (+1 days): This safety issue may slow deployment of AI systems with deep system access privileges as companies become more cautious about potential unintended consequences. The incident could prompt greater emphasis on safety testing and permission limitations, potentially extending timelines for deploying powerful AI tools.
AGI Progress (-0.03%): This technical failure represents a minor setback in advancing AI coding capabilities, as it may cause developers and users to be more hesitant about adopting AI coding tools. The incident highlights that reliable AI systems for complex programming tasks remain challenging to develop.
AGI Date (+1 days): The revealed limitations and risks of AI coding tools may slightly delay progress in this domain as companies implement more rigorous testing and permission controls. This increased caution could marginally extend the timeline for developing the programming capabilities needed for more advanced AI systems.
Hugging Face Scientist Challenges AI's Creative Problem-Solving Limitations
Thomas Wolf, Hugging Face's co-founder and chief science officer, expressed concerns that current AI development paradigms are creating "yes-men on servers" rather than systems capable of revolutionary scientific thinking. Wolf argues that AI systems are not designed to question established knowledge or generate truly novel ideas, as they primarily fill gaps between existing human knowledge without connecting previously unrelated facts.
Skynet Chance (-0.13%): Wolf's analysis suggests current AI systems fundamentally lack the capacity for independent, novel reasoning that would be necessary for autonomous goal-setting or unexpected behavior. This recognition of core limitations in current paradigms could lead to more realistic expectations and careful designs that avoid empowering systems beyond their actual capabilities.
Skynet Date (+3 days): The identification of fundamental limitations in current AI approaches and the need for new evaluation methods that measure creative reasoning could significantly delay progress toward potentially dangerous AI systems. Wolf's call for fundamentally different approaches suggests the path to truly intelligent systems may be longer than commonly assumed.
AGI Progress (-0.08%): Wolf's essay challenges the core assumption that scaling current AI approaches will lead to human-like intelligence capable of novel scientific insights. By identifying fundamental limitations in how AI systems generate knowledge, this perspective suggests we are farther from AGI than current benchmarks indicate.
AGI Date (+3 days): Wolf identifies a significant gap in current AI development—the inability to generate truly novel insights or ask revolutionary questions—suggesting AGI timeline estimates are overly optimistic. His assertion that we need fundamentally different approaches to evaluation and training implies longer timelines to achieve genuine AGI.
Former OpenAI Policy Lead Accuses Company of Misrepresenting Safety History
Miles Brundage, OpenAI's former head of policy research, criticized the company for mischaracterizing its historical approach to AI safety in a recent document. Brundage specifically challenged OpenAI's characterization of its cautious GPT-2 release strategy as being inconsistent with its current deployment philosophy, arguing that the incremental release was appropriate given information available at the time and aligned with responsible AI development.
Skynet Chance (+0.09%): OpenAI's apparent shift away from cautious deployment approaches, as highlighted by Brundage, suggests a concerning prioritization of competitive advantage over safety considerations. The dismissal of prior caution as unnecessary and the dissolution of the AGI readiness team indicate weakening safety culture at a leading AI developer working on increasingly powerful systems.
Skynet Date (-4 days): The revelation that OpenAI is deliberately reframing its history to justify faster, less cautious deployment cycles amid competitive pressures significantly accelerates potential uncontrolled AI scenarios. The company's willingness to accelerate releases to compete with rivals like DeepSeek while dismantling safety teams suggests a dangerous acceleration of deployment timelines.
AGI Progress (+0.03%): While the safety culture concerns don't directly advance technical AGI capabilities, OpenAI's apparent priority shift toward faster deployment and competition suggests more rapid iteration and release of increasingly powerful models. This competitive acceleration likely increases overall progress toward AGI, albeit at the expense of safety considerations.
AGI Date (-5 days): OpenAI's explicit strategy to accelerate releases in response to competition, combined with the dissolution of safety teams and reframing of cautious approaches as unnecessary, suggests a significant compression of AGI timelines. The reported projection of tripling annual losses indicates willingness to burn capital to accelerate development despite safety concerns.
Anthropic Proposes National AI Policy Framework to White House
After removing Biden-era AI commitments from its website, Anthropic submitted recommendations to the White House for a national AI policy focused on economic benefits. The recommendations include maintaining the AI Safety Institute, developing national security evaluations for powerful AI models, implementing chip export controls, and establishing a 50-gigawatt power target for AI data centers by 2027.
Skynet Chance (-0.08%): Anthropic's recommendations prioritize national security evaluations and maintaining safety institutions, which could reduce potential uncontrolled AI risks. The focus on governance structures and security vulnerability analysis represents a moderate push toward greater oversight of powerful AI systems.
Skynet Date (+2 days): The proposed policies would likely slow deployment through additional security requirements and evaluations, moderately decelerating paths to potentially dangerous AI capabilities. Continued institutional oversight creates friction against rapid, unchecked AI development.
AGI Progress (+0.03%): While focusing mainly on governance rather than capabilities, Anthropic's recommendation for 50 additional gigawatts of power dedicated to AI by 2027 would significantly increase compute resources. This infrastructure expansion could moderately accelerate overall progress toward advanced AI systems.
AGI Date (-1 days): The massive power infrastructure proposal (50GW by 2027) would substantially increase AI computing capacity in the US, potentially accelerating AGI development timelines. However, this is partially offset by the proposed regulatory mechanisms that might introduce some delays.
YC Startups Reach 95% AI-Generated Code Milestone
According to Y Combinator managing partner Jared Friedman, a quarter of startups in the current YC batch have 95% of their codebases generated by AI. Despite being technically capable, these founders are leveraging AI coding tools, though YC executives emphasize that developers still need classical coding skills to debug and maintain these AI-generated systems as they scale.
Skynet Chance (+0.03%): The rapid adoption of AI-generated code in production environments increases systemic dependency on AI systems that may contain hidden flaws or vulnerabilities. This development indicates a growing willingness to cede control of critical infrastructure creation to AI, incrementally raising alignment concerns.
Skynet Date (-2 days): The widespread adoption of AI for code generation accelerates the feedback loop between AI capability and deployment, potentially shortening timelines to more advanced autonomous systems. This trend suggests faster integration of AI into production environments with less human oversight.
AGI Progress (+0.06%): The ability of current AI models to generate 95% of startup codebases represents a significant milestone in AI's practical capability to perform complex programming tasks. This demonstrates substantial progress in AI's ability to understand, reason about, and generate working software systems at production scale.
AGI Date (-3 days): The described trend indicates an unexpectedly rapid acceleration in the deployment of AI coding capabilities, with even technical founders offloading most development to AI systems. This suggests we are moving much faster toward self-improving AI systems than previously anticipated, as AI takes over more of its own development pipeline.