Lifeboat Foundation

Amidst rapid technological advancements, Tiny AI is emerging as a silent powerhouse. Imagine algorithms compressed to fit microchips yet capable of recognizing faces, translating languages, and predicting market trends. Tiny AI operates discreetly within our devices, orchestrating smart homes and propelling advancements in personalized medicine.

Tiny AI excels in efficiency, adaptability, and impact by utilizing compact neural networks, streamlined algorithms, and edge computing capabilities. It represents a form of artificial intelligence that is lightweight, efficient, and positioned to revolutionize various aspects of our daily lives.

Looking into the future, quantum computing and neuromorphic chips are new technologies taking us into unexplored areas. Quantum computing works differently than regular computers, allowing for faster problem-solving, realistic simulation of molecular interactions, and quicker decryption of codes. It is not just a sci-fi idea anymore; it’s becoming a real possibility.

In the rapidly evolving landscape of artificial intelligence, the quest for hardware that can keep pace with the burgeoning computational demands is relentless. A significant breakthrough in this quest has been achieved through a collaborative effort spearheaded by Purdue University, alongside the University of California San Diego (UCSD) and École Supérieure de Physique et de Chimie Industrielles (ESPCI) in Paris. This collaboration marks a pivotal advancement in the field of neuromorphic computing, a revolutionary approach that seeks to emulate the human brain’s mechanisms within computing architecture.

The Challenges of Current AI Hardware

The rapid advancements in AI have ushered in complex algorithms and models, demanding an unprecedented level of computational power. Yet, as we delve deeper into the realms of AI, a glaring challenge emerges: the inadequacy of current silicon-based computer architectures in keeping pace with the evolving demands of AI technology.

Scientific Reports –a crucial aspect of language acquisition. Prior experimental studies proved that artificial grammars can be learnt by human subjects after little exposure and often without explicit knowledge of the underlying rules. We tested four grammars with different complexity levels both in humans and in feedforward and recurrent networks. Our results show that both architectures can “learn” (via error back-propagation) the grammars after the same number of training sequences as humans do, but recurrent networks perform closer to humans than feedforward ones, irrespective of the grammar complexity level. Moreover, similar to visual processing, in which feedforward and recurrent architectures have been related to unconscious and conscious processes, the difference in performance between architectures over ten regular grammars shows that simpler and more explicit grammars are better learnt by recurrent architectures, supporting the hypothesis that explicit learning is best modeled by recurrent networks, whereas feedforward networks supposedly capture the dynamics involved in implicit learning.

Herbert Ong Brighter with Herbert.

In the first clinical trial of a targeted pharmacologic therapeutic for mild traumatic brain injury in pediatric patients, scientists from the Minds Matter Concussion Frontier Program at Children’s Hospital of Philadelphia (CHOP) have found preliminary evidence that adolescents and young adults with concussion who take a specific formulation of branched-chain amino acid (BCAA) supplements after injury experience faster symptom reduction and return to physical activity.

One shaken Redditor took to r/teslamotors to share their story after their Tesla vehicle saved them from a situation that could easily have turned deadly.

“My Model 3 saved my life today,” they said in the post.

According to the Redditor, they were driving home on the highway in heavy, “basically stopped” traffic. They wanted to change lanes, but the number of cars was making it difficult. “Problem was there were a lot of oncoming cars and almost no breaks in between them,” they said.

Anime Production Inspired Real-World Anime Super-Resolution https://huggingface.co/papers/2403.

demo:

While real-world anime super-resolution (SR) has gained increasing attention in the SR community, existing methods still adopt techniques…

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A team of Northwestern University scientists has developed the first wireless, implantable temperature sensor to detect inflammatory flareups in patients with Crohn’s disease. The approach offers long-term, real-time monitoring and could enable clinicians to act earlier to prevent or limit the permanent damage caused by inflammatory episodes.

A new obesity treatment triggered weight loss in mice, even as they continued to eat a diet high in fat, sugar, and cholesterol. While much more research is needed, it suggests that it may be possible for people to one day lose weight while still enjoying the foods they want.

The challenge: By 2020, nearly 1 billion people had body mass indexes (BMIs) in the obese range, and if current trends continue, more than 50% of the global population will be obese or overweight by 2035.

This means the majority of people on Earth will be at higher risk of serious health problems related to weight, including stroke, diabetes, hypertension, and some cancers.