Deep learning and global workspace theory.
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1-s2.0-S0166223621000771-am.pdf
Posted in robotics/AI
PHI_575-Dennett.pdf
Posted in neuroscience
When_HAL_Kills.pdf
Posted in computing, ethics | 1 Comment on When_HAL_Kills.pdf
An exploration of a potential solution to the Fermi Paradox within the Cambrian explosion period of geologic history, with an aside about fossil preservation in space.
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Taxonomy of principal distances and divergences v/ Frank Nielsen.
We define duo Bregman divergences, duo Fenchel-Young divergences, duo Jensen divergences. We show how those divergences occur naturally when calculating the Kullback-Leibler divergence and skew Bhattacharyya distances between densities belonging to nested exponential families. We report the KLD between truncated normal distributions as a duo Bregman divergence. Demo code:
Microsoft, Alphabet, OpenAI, Nvidia CEOs join US advisory board to advise on protecting critical infrastructure from AI threats. Board aims to prevent AI-related disruptions to national security and public safety.
Assessing AI risks in the context of their use, rather than as inherent in the technologies themselves, leads to smarter and safer implementations.
The number of quantum computing use cases is growing. Using a combination of quantum computing technologies might propel companies looking to stay ahead of the curve in their respective industries.
Before his recent death, the influential philosopher Daniel Dennett spoke to the BBC about why he saw new dangers from AI.
Through years of engineering gene-editing systems, researchers have developed a suite of tools that enable the modification of genomes in living cells, akin to “genome surgery.” These tools, including ones based on a natural system known as CRISPR/Cas9, offer enormous potential for addressing unmet clinical needs, underscored by the recent FDA approval of the first CRISPR/Cas9-based therapy.
A relatively new approach called “prime editing” enables gene-editing with exceptional accuracy and high versatility, but has a critical tradeoff: variable and often low efficiency of edit installation. In other words, while prime edits can be made with high precision and few unwanted byproducts, the approach also often fails to make those edits at reasonable frequencies.
In a paper that appeared in print in the journal Nature on April 18, 2024, Princeton scientists Jun Yan and Britt Adamson, along with several colleagues, describe a more efficient prime editor.