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Not ideal!


In January, multi-hyphenate billionaire Elon Musk announced that his brain-computer interface startup Neuralink had successfully implanted a wireless brain chip into a human subject for the first time.

Over the next couple of months, 29-year-old Noland Arbaugh was shown moving a cursor with his mind, playing Civilization VI and even a fast-paced round of Mario Kart.

But as the Wall Street Journal reports, there have been complications behind the scenes. After it reached out to Neuralink, the company conceded in a blog post that there have been issues with the implant.

Each CRISPR system has two parts: a strand of RNA that matches the target and a protein that makes the edit. The most commonly used protein for gene editing is called “Cas9,” but scientists have discovered CRISPRs with other proteins that give them unique capabilities — while CRISPR-Cas9 slices through DNA, for example, CRISPR-Cas13 targets RNA.

Our current CRISPR gene editors are far from perfect, though. They can make edits in the wrong places or edit too few cells to make a difference, so researchers are constantly on the hunt for new CRISPR systems.

AI-designed CRISPR: Up until now, that hunt has been limited to the CRISPRs that have been discovered in nature, but Profluent has used the same types of AI models that allow ChatGPT to generate language to develop an AI platform that can generate millions of CRISPR-like proteins.

Reconstruction of 1 mm3 of human brain (at 1.4 petabytes of EM data) published by @stardazed0 (@GoogleAI) & Lichtman lab.

Paper: https://science.org/doi/10.1126/science.adk4858

Blog:


Marking ten years of connectomics research at Google, we are releasing a publication in Science about a reconstruction at the synaptic level of a small piece of the human brain. We discuss the reconstruction process and dataset, and we present several new neuron structures discovered in the data.

Demis Hassabis, the CEO of Google Deepmind, expects AI systems in the near future to not only answer questions but also plan and act independently.

In an interview with Bloomberg, Hassabis says his company is working on such “agent-like” systems that could be ready for use in one to two years.

“I’m really excited about the next stage of these large general models. You know, I think the next things we’re going to see perhaps this year, maybe next year, is more agent like behavior,” says Hassabis.