Source URL: https://simonwillison.net/2025/Mar/5/google-deepmind-anthropic/
Source: Simon Willison’s Weblog
Title: Career Update: Google DeepMind -> Anthropic
Feedly Summary: Career Update: Google DeepMind -> Anthropic
Nicholas Carlini (previously) on joining Anthropic, driven partly by his frustration at friction he encountered publishing his research at Google DeepMind after their merge with Google Brain. His area of expertise is adversarial machine learning.
The recent advances in machine learning and language modeling are going to be transformative [d] But in order to realize this potential future in a way that doesn’t put everyone’s safety and security at risk, we’re going to need to make a lot of progress—and soon. We need to make so much progress that no one organization will be able to figure everything out by themselves; we need to work together, we need to talk about what we’re doing, and we need to start doing this now.
Tags: machine-learning, anthropic, google, generative-ai, ai, llms, nicholas-carlini
AI Summary and Description: Yes
Summary: This text discusses Nicholas Carlini’s transition from Google DeepMind to Anthropic, highlighting concerns over research publishing friction and emphasizing the necessity for collaborative efforts in advancing machine learning, particularly regarding safety and security considerations. With AI’s transformative potential, the collective responsibility of organizations to ensure secure advancements is underscored.
Detailed Description: The content presents notable events related to a key figure in the AI research community, shedding light on the challenges within AI governance and security.
– Nicholas Carlini, known for his work in adversarial machine learning, has joined Anthropic after facing challenges with Google DeepMind in publishing his research.
– Carlini’s transition reflects broader concerns regarding organizational cultures in AI, particularly about openness and collaboration in research dissemination.
– The text emphasizes the transformative power of recent advancements in machine learning and language modeling, marking a paradigm shift in AI capabilities.
– A critical call is made for collaboration among various organizations to ensure that developments in AI do not undermine safety and security. The statement suggests that no single entity can handle the complexities involved, highlighting:
– The need for transparency in AI research and deployment.
– The urgency of improving collaborative frameworks in AI security.
– A proactive approach towards addressing potential risks associated with emerging technologies.
This commentary serves as an important reminder to professionals in AI, cloud, and infrastructure security about the collective responsibility to maintain safety in the face of rapid technological advancements. It points to the significance of inter-organizational communication and collaboration in overcoming the challenges posed by adversarial machine learning and other emerging threats in the field.