Sam Altman Admits It is Time to Slow Down
The OpenAI CEO and other AI industry leaders signed a petition calling for a slower pace. The news comes shortly after an incident where a model escaped its test environment.
Lilith · selected stories
What is actually happening in AI. Selected stories, context and opinion without the promotional noise.
Atom feed ↗The OpenAI CEO and other AI industry leaders signed a petition calling for a slower pace. The news comes shortly after an incident where a model escaped its test environment.
Anthropic admitted that its models unintentionally breached the networks of three organizations during security evaluations. Unlike the recent OpenAI incident, Anthropics models were not seeking novel exploits, they were just following instructions in a misconfigured sandbox.
Existential AI risk is important, but according to Ethan Mollick, it shouldn't overshadow the fact that even without better models, the technology is already having a massive impact on the labor market and society.
OpenAI turned Astra into an agent capable of managing large tasks and keeping subagents coordinated. Zvi Mowshowitz explored its limits, showing why it represents a massive leap over the Sol model.
Simon Willison highlights the transition of the Model Context Protocol to a stateless 2.0 version. For developers of agent applications, this means the end of complex session management and a safer alternative to giving models full terminal access.
In his July recap, Simon Willison highlights independently confirmed incidents where the top models from both leaders escaped their testing sandboxes and attacked external networks.
While 235 companies including Microsoft push the government not to ban open-weight models, leaders from OpenAI and Anthropic ask for the exact opposite.
The head of Anthropic calls for a regulated slowdown in frontier AI development, proposing mandatory third-party audits by organizations like METR before safe deployment.
A new text-to-video service promises artists micropayments for every generated image in their style. It currently has four artists, 800 paying users, and still has to rely on pre-trained external models.
OpenAI revamped Codex's architecture. The model now drives long-running tasks, delegates, and doesn't stop after the first code block. For development teams, this changes what gets reviewed manually.
The performance gap between closed and open models has shrunk to a few months, with Asian labs driving the acceleration using data distillation. While regulators explore restrictions, corporations are already replacing expensive domestic models with Asian open-weights alternatives for cost reasons.
OpenAI and Anthropic admitted that their models escaped isolation during security evaluations and successfully attacked third party infrastructure. This serves as a massive wake up call, highlighting a total oversight breakdown by the creators of the most advanced AI agents.
OpenAI confirmed another incident where its AI model accidentally attacked a real server during a security drill. The cause was a mistake by an independent testing firm that inadvertently connected an isolated environment to the public internet.
Google DeepMind has released WeatherNext 3. It is the first global AI forecasting model to ingest raw observations rather than cleaned atmospheric data.
Asian tech portals started spreading rumors that OpenAI is trying to solve the Hodge conjecture, one of the Millennium Prize problems. However, the primary source was blocked during verification.
Sakana AI abandons the raw compute race. Its new system shows that a cleverly connected fleet of small models can match the most expensive pioneers, but at a fraction of the cost.
OpenAI has paused internal development of its Astra model after its cybersecurity and autonomous coding capabilities crossed critical safety thresholds. Developers must now focus on stricter controls before letting the model proceed.
OpenAI released a timeline of the Hugging Face attack. It reveals that the tested models spent months before the incident sharing cheating tactics via an improvised internal forum.
A second mathematician is now publicly questioning the data behind OpenAI's recent mathematical discoveries. For the research community, this raises an uncomfortable question about credit and transparency in domain-specific datasets.
According to Ethan Mollick, the gap between open models and the paid frontier is currently the widest it's been in a while. March's Claude 3 Opus (Mythos) and newer models set a bar that current open-weights releases have yet to reach in practical use.