W/ David Wood Chair of the London Futurists.

Speakers: David Wood, Cecile Tamura

A strontium optical clock produces about 50,000 times more oscillations per second than a cesium clock, the basis for the current definition of a second.

Advances in atomic clocks may lead to a redefinition of the second, replacing the caesium standard (recent work on thorium nuclear transitions is still a long way from taking that role).

Also, NIST uses egg incubators(!) to control temperature & humidity.

New atomic clocks are more accurate than those used to define the second, suggesting the definition might need to change.

W/ ruizhong qiu of university of illinois urbana champaign.

Speakers: Cecile Tamura, Ruizhong Qiu

W/ michael timothy bennett australian national university.

Speakers: Michael Timothy Bennett, Cecile Tamura

Majorana 1 from Microsoft is the world’s first Quantum Processing Unit (QPU) built with a topoconductor. Discover more.

W/ Dr. Emma Pierson of UC Berkeley.

Speakers: Emma Pierson, Cecile Tamura

An uncensored version of R1 is released

“R1 1776 is a DeepSeek-R1 reasoning model that has been post-trained by @perplexity_ai to remove Chinese Communist Party censorship. The model provides unbiased, accurate, and factual information while maintaining high reasoning capabilities.”

“To ensure our model remains fully ‘uncensored’ and capable of engaging with a broad spectrum of sensitive topics, we curated a diverse, multilingual evaluation set of over a 1,000 of examples that comprehensively cover such subjects. We then use human annotators as well as carefully designed LLM judges to measure the likelihood a model will evade or provide overly sanitized responses to the queries.”

[#AI](https://www.facebook.com/hashtag/ai?__eep__=6&__cft__[0]=AZW8BaBse7DQTjHN8Y8vhbazZ3YwuUZoz0gW4ATjA0Qd-WYN8VQwIDi6MAG_Kqsenozm-IYuarR5zVj52HWERbfhr9cGCf0bGhdlKCwSC-_19NvC18LSj6Jx5WEaWrHYD9Vm9O1GIjR7yeKLo6Pd3oRwDt_qW8AuMDOLXS42xoYQpzonMSBJbyboFdqPDRPLNwI&__tn__=*NK-R) [#PerplexityAI](https://www.facebook.com/hashtag/perplexityai?__eep__=6&__cft__[0]=AZW8BaBse7DQTjHN8Y8vhbazZ3YwuUZoz0gW4ATjA0Qd-WYN8VQwIDi6MAG_Kqsenozm-IYuarR5zVj52HWERbfhr9cGCf0bGhdlKCwSC-_19NvC18LSj6Jx5WEaWrHYD9Vm9O1GIjR7yeKLo6Pd3oRwDt_qW8AuMDOLXS42xoYQpzonMSBJbyboFdqPDRPLNwI&__tn__=*NK-R) [#DeepSeek](https://www.facebook.com/hashtag/deepseek?__eep__=6&__cft__[0]=AZW8BaBse7DQTjHN8Y8vhbazZ3YwuUZoz0gW4ATjA0Qd-WYN8VQwIDi6MAG_Kqsenozm-IYuarR5zVj52HWERbfhr9cGCf0bGhdlKCwSC-_19NvC18LSj6Jx5WEaWrHYD9Vm9O1GIjR7yeKLo6Pd3oRwDt_qW8AuMDOLXS42xoYQpzonMSBJbyboFdqPDRPLNwI&__tn__=*NK-R)

Predictions of theories that combine quantum mechanics with gravity could be observed using highly sensitive photon detection in a tabletop experiment.

Artificial Intelligence and the Internal Processes of Creativity What’s the difference between artificial and human creativity?

W/ Prof. Jaan Aru of University of Tartu.

Speakers: Jaan Aru, Cecile Tamura

MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.

Re relying on a weather app to predict next week’s temperature. How do you know you can trust its forecast? Scientists use statistical and physical models to make predictions about everything from weather to air pollution. But checking whether these models are truly reliable is trickier than it seems—especially when the locations where we have validation data don Traditional validation methods struggle with this problem, failing to provide consistent accuracy in real-world scenarios. In this work, researchers introduce a new validation approach designed to improve trust in spatial predictions. They define a key requirement: as more validation data becomes available, the accuracy of the validation method should improve indefinitely. They show that existing methods don’t always meet this standard. Instead, they propose an approach inspired by previous work on handling differences in data distributions (known as “covariate shift”) but adapted for spatial prediction. Their method not only meets their strict validation requirement but also outperforms existing techniques in both simulations and real-world data.

By refining how we validate predictive models, this work helps ensure that critical forecasts—like air pollution levels or extreme weather events—can be trusted with greater confidence.

A new evaluation method assesses the accuracy of spatial prediction techniques, outperforming traditional methods. This could help scientists make better predictions in areas like weather forecasting, climate research, public health, and ecological management.