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Neural microtissues derived from pluripotent stem cells (iPSCs) can replace dopaminergic neurons, the nerve cells that are lost in Parkinson’s disease, and restore motor function when grown into tiny capsules and transplanted into the brains of model rats, a study led by TreeFrog Therapeutics found.

“TreeFrog Therapeutics has overcome the most complex challenges of developing a successful treatment for Parkinson’s disease using our C-Stem platform technology and producing a therapy containing mature dopaminergic neurons with a unique 3D format that promotes cell survival post-graft with proven pre-clinical results,” Jens Schroeder, MD, PhD, TreeFrog’s chief medical officer, said in a company press release.

The study, “Bioreactor-produced iPSCs-derived dopaminergic neuron-containing neural microtissues innervate and normalize rotational bias in a dose-dependent manner in a Parkinson rat model,” was published in Neurotherapeutics.

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Quantum memory lets a quantum computer perform a task not necessarily with fewer steps, but with less data. Could this in itself be a way to prove quantum advantage?

The new papers show that quantum memory lets a quantum computer perform a task not necessarily with fewer steps, but with less data. As a result, researchers believe this in itself could be a way to prove quantum advantage. “It allows us to, in the more near term, already achieve that kind of quantum advantage,” said Hsin-Yuan Huang, a physicist at Google Quantum AI.

But researchers are excited about the practical benefits too, as the new results make it easier for researchers to understand complex quantum systems.

“We’re edging closer to things people would really want to measure in these physical systems,” said Jarrod McClean, a computer scientist at Google Quantum AI.

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Predibase announces the Predibase Inference Engine, their new infrastructure offering designed to be the best platform for serving fine-tuned small language models (SLMs). The Predibase Inference Engine dramatically improves SLM deployments by making them faster, easily scalable, and more cost-effective for enterprises grappling with the complexities of productionizing AI. Built on Predibase’s innovations–Turbo LoRA and LoRA eXchange (LoRAX)–the Predibase Inference Engine is designed from the ground up to offer a best-in-class experience for serving fine-tuned SLMs.

The need for such an innovation is clear. As AI becomes more entrenched in the fabric of enterprise operations, the challenges associated with deploying and scaling SLMs have grown increasingly daunting. Homegrown infrastructure is often ill-equipped to handle the dynamic demands of high-volume AI workloads, leading to inflated costs, diminished performance, and operational bottlenecks. The Predibase Inference Engine addresses these challenges head-on, offering a tailor-made solution for enterprise AI deployments.

Join Predibase webinar on October 29th to learn more about the Predibase Inference Engine!

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