AIhub monthly digest: August 2026 - IJCAI-ECAI in Bremen, the mathematics of simplicity, and does AI change the way we think? Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we report on events at IJCAI-ECAI 2026, learn about the mathematics of simplicity, investigate the accountability vacuum, and find out how AI changes the way we think. On Rashomon sets, the mathematics of simplicity, and why we don't need black boxes: an interview with Cynthia Rudin In the latest in our series of interviews with AI pioneers, we hear from Cynthia Rudin about interpretability, noise, and the case against complexity for complexity's sake. The 35th International Joint Conference on Artificial Intelligence and the 29th European Conference on Artificial Intelligence (IJACI-ECAI 2026) was held from 15-21 August, in Bremen, Germany.

If the memory state can be addressed by its content, itisfurthermore called content-addressable.

The Goldilocks phase is reminiscent of "intelligence from starvation" in Darwinian evolution, where resource limitations drivediscoveryofmore efficient solutions.

However, since this decoder effectively approximates thenth derivative of the input vector, it is very sensitive to noise. In our framework, the input is often very noisy, since it corresponds to the converging points of different learning traces. In this section we describe two linear decoders that differ from that in [35] and are more noise-resilient. A.9 and A.10 is crucial for long temporal horizons, since regularization causes the overall magnitude of the recoveredτ-space to decrease asτ increases3. Normalization amends thedecreasing magnitude problem bymaking theτ-space to sum to 1 for everyτ.

In fact, the bound can be improved by considering a data-dependent measure, e.g., Rademacher