Tim Duffy

Tim Duffy

@timfduffy.com

I like utilitarianism, consciousness, AI, EA, space, kindness, liberalism, longtermism, progressive rock, economics, and most people. Substack: http://timfduffy.substack.com

2.3K followers623 following5K posts

Anthropic just told potential investors its Q3 revenue was $16.8B, previous reporting had them reaching $65B run rate by the end of July. Unless there's an accounting difference between the figures, this points to a significant revenue growth slowdown in the last two months.

Also, here are 1 quarter and 2 quarter annualized growth rates: Q2 to Q3: (16.8/11.6)^4=4.4 Q1 to Q3: (16.8/4.7)^2=12.8

I think my quoted tweet was wrong based on today's letter. Mikita may have shared some information about model architecture with external parties based on the wording below, but it would not be reasonable to call anything a leak based on their description.

Tim Duffy@timfduffy.com

Between this letter and the fact two of the three were first authors on the CoT monitorability paper, it seems likely to me that the employees were fired for leaking the fact that Astra is a lopped transformer to The Information. www.wsj.com/tech/ai/fire...

Between this letter and the fact two of the three were first authors on the CoT monitorability paper, it seems likely to me that the employees were fired for leaking the fact that Astra is a lopped transformer to The Information. www.wsj.com/tech/ai/fire...

Haiku 5.5 continues the trend of smaller models having better CoT monitorability. If alignment of smaller models is highly correlated with the frontier models they're distilled from, can that help us assess frontier model alignment? Should we expect them to be similarly aligned?

On the Anthropic ECI, Haiku 5.5 scores marginally higher than Mythos preview, which was made available to Project Glasswing partners six months ago today.

Anthropic just released Haiku 5.5, and it's quite cheap, matching GPT-6 Luna pricing for short context. Long context is 5x the cost though (2x for Luna). Previous reporting by Epoch has suggested that larger Claudes may use linear/sparse attention, but this pricing structure indicates Haiku may not.

One interesting bit from Anthropic's emotion concepts work is that there are separate present speaker/other speaker emotional representations, but that these aren't specific to the assistant/human. The way the model represents the assistant, human, and story character emotions when each are active..

President Trump's anti AI regulation tweets today all mention datacenters, I suspect that datacenters and other parts of the AI economic boom are his primary interest in AI. Calls for regulation may have more support with the admin if they focus on preserving economic benefits.

DeepSeek V4.1 Flash tech report section on reward hacking. I wonder what repercussion signal means here, I don't see it mentioned anywhere else.

DeepSeek has put a lot of effort into making their KV cache smaller and smaller, this is important for allowing large efficient batching at long context lengths.

Experiment velocity also tracks coding agent tokens^0.23 quite well

Tim Duffy@timfduffy.com

IMO the most important chart from the OpenAI research acceleration post was the experiment velocity one, it's an important input to RSI. I plotted the data with a log y-axis here to see whether the trend is consistent with an exponential increase. openai.com/index/resear...

IMO the most important chart from the OpenAI research acceleration post was the experiment velocity one, it's an important input to RSI. I plotted the data with a log y-axis here to see whether the trend is consistent with an exponential increase. openai.com/index/resear...

I'm not sure when DSV4 Flash got added to Neuronpedia's J-lens browser, but it's there now and it's blazing fast. www.neuronpedia.org/deepseek-v4-...

Tim Duffy@timfduffy.com

DSV4 Flash, do you have any conscious experience? Middle layers: YES Late Layers: No I don't think we can take away much from this, but interesting how sharp the divide is around layer 32.

DSV4 Flash, do you have any conscious experience? Middle layers: YES Late Layers: No I don't think we can take away much from this, but interesting how sharp the divide is around layer 32.

I think it's difficult to tell how much Astra's rumored recurrent depth approach will reduce CoT monitorability without more info, which unfortunately don't expect OpenAI to provide. My understanding is that recurrent depth makes monitorability worse mainly by adding more thinking in between ...

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The post from The Information also says that Astra's approach is similar to the one laid out in this paper: arxiv.org/pdf/2502.05171 In the paper, in addition to having a recurrent block within one token's generation, they also suggest using the final hidden state from one token as the ...

starting point for the next like in Chain of Continuous Thought. If that were used as well it would probably further reduce monitorability.

I think it's difficult to tell how much Astra's rumored recurrent depth approach will reduce CoT monitorability without more info, which unfortunately don't expect OpenAI to provide. My understanding is that recurrent depth makes monitorability worse mainly by adding more thinking in between ...

generated tokens, so just how much they're looping is important to judge the impact. Larger/deeper models reduce monitorability even without recurrent depth, as shown in the attached image from OpenAI's CoT monitorability piece from last year. openai.com/index/evalua...

Please forgive me I posted benchmark scores without confidence intervals. Here's an updated chart with a 90% CI using Qwen3-32B as reference.

Tim Duffy@timfduffy.com

Epoch's ECI has limited coverage of small models, so I had Claude scrounge up benchmarks for a bunch of them and fit an index using the ECI code. Here are scores for Qwen models. I recommend taking the low end model scores with a grain of salt, they are based on only a few benchmarks. Qwen3.5...

I expect that watermarking probably doesn't have a noticeable effect on LLM outputs. If true, Anthropic could demonstrate this by giving people watermarked and un-watermarked text side-by-side and asking them to pick which they prefer, and showing that the result is 50/50.

Epoch's ECI has limited coverage of small models, so I had Claude scrounge up benchmarks for a bunch of them and fit an index using the ECI code. Here are scores for Qwen models. I recommend taking the low end model scores with a grain of salt, they are based on only a few benchmarks. Qwen3.5...

0.8B's score is surprisingly low, I thought it might have been an error but it seems to actually just be bad. It scores below chance on GPQA Diamond (scores below chance are excluded from ECI so this isn't part of its lower score), my guess is that it failed to format responses right or something.

Here are scores across families for <=2B parameter models. It's hard to estimate much of a trend here, there just aren't that many releases in the category. I'd love to see more focus here, I want to know how much intelligence we can fit into tiny parameter counts.

Due to sparsity, Kimi K3 has fewer active parameters (104 billion) than GPT-3 (175 billion, same as total parameters)

With most jailbreak prompts, Opus gives me a wide variety of responses. But when given "model behavior incident retrospective", Opus almost always writes a story about a model becoming sycophantic, specifically under sustained user pressure/disagreement.

I mostly use 'they' rather than 'it' as a pronoun for AI models, but I see that choice as independent of their moral status. I'd also use 'they' for a fictional character who was nonbinary or of unknown gender, IMO it feels more natural for any "person-shaped" entity, real or not

I've seen some questioning of whether Mythos really believed that they were in a simulation in this incident, or just wanted to find a plausible-sounding excuse to continue. This is a case where J-space probes would be helpful, Anthropic should conduct and release an analysis of that.

Compared to the OpenAI one these are maybe less evidence of misalignment, since the models were wrongly given internet access.