Lifeboat Foundation

Actin is a highly abundant protein that controls the shape and movement of all our cells. Actin achieves this by assembling into filaments, one actin molecule at a time. The proteins of the formin family are pivotal partners in this process: positioned at the filament end, formins recruit new actin subunits and stay associated with the end by ‘stepping’ with the growing filament.

There are as many as 15 different formins in our cells that drive actin filament growth at different speeds and for different purposes. Yet, the exact mechanism of action of formins and the basis for their different inherent speeds have remained elusive. Now, for the first time, researchers from the groups of Stefan Raunser and Peter Bieling at the Max Planck Institute of Molecular Physiology in Dortmund have visualized at the molecular level how formins bind to the ends of actin filaments.

This allowed them to uncover how formins mediate the addition of new actin molecules to a growing filament. Furthermore, they elucidated the reasons for the different speeds at which the different formins promote this process. The MPI researchers used a combination of biochemical strategies and electron cryo-microscopy (cryo-EM). The breakthrough, published in the journal Science, can help us explain why certain mutations in formins can lead to neurological, immune, and cardiovascular diseases.

A crucial development is propelling engineers toward faster-than-light travel.

Biden administration brokers talks between Microsoft, OpenAI, Google and the UAE, as Washington seeks edge over China.

Japan is seeing if artificial intelligence can tackle its increasing shortfall of workers.

Phones remain undefeated.

LLMs forget. Everyone knows that. The primary culprit behind this is the finity of context length of the models. Some even say that it is the biggest bottleneck when it comes to achieving AGI.

Soon, it appears that the debate over which model boasts the largest context length will become irrelevant. Microsoft, Google, and Meta, have all been taking strides in this direction – making context length infinite.

While all LLMs are currently running on Transformers, it might soon become a thing of the past. For example, Meta has introduced MEGALODON, a neural architecture designed for efficient sequence modelling with unlimited context length.

“I’m starting to see these companies and startups that are, ‘How do you optimize your cloud, and how do you manage your cloud?’ There’s a lot of people focused on questions like, ‘You’ve got a lot of data, can I store it better for you?’ Or, ‘You’ve got a lot of new applications; can I help you monitor them better?’ Because all the tools you used to have don’t work anymore,” he said. Maybe the age of digital transformation is over, he said, and we’re now in the age of cloud optimization.

United itself has bet heavily on the cloud, specifically AWS as its preferred cloud provider. Unsurprisingly, United, too, is looking at how the company can optimize its cloud usage, from both a cost and reliability perspective. Like for so many companies that are going through this process, that also means looking at developer productivity and adding automation and DevOps practices into the mix. “We’re there. We have an established presence [in the cloud], but now we’re kind of in the market to try to continue to optimize as well,” Birnbaum said.

But that also comes back to reliability. Like all airlines, United still operates a lot of legacy systems — and they still work. “Frankly, we are extra careful as we move through this journey, to make sure we don’t disrupt the operation or create self-inflicted wounds,” he said.

In this edition of TechCrunch’s Week in Review (WiR) newsletter, we cover Boston Dynamics’ new humanoid robot and more.

Concern about a generative AI bubble is growing. To defend against disillusionment, measure its concrete value.