AI News You Probably Missed In May 

AI continues to amaze us. And the AI news for this month is no exception.

As it makes groundbreaking strides across various industries and delivers subtle, yet remarkable advancements, we’re seeing it unfold as a major benefit to humanity. 

Robotic companions aiding dementia patients. Major energy reductions in data centre chips. Autonomous robots that can run up to 10,000 experiments a day. These developments are reshaping everything from healthcare to scientific discovery. 

But keeping up with all the crazy new advancements can be a pain. Especially when there are so many sources to choose from. 

So we’re giving you a round-up of some of the remarkable AI news and innovations from May. The ones that may have slipped under your radar. 

Let’s dive into a few of the incredible AI breakthroughs through May.

Robotic Companions for Dementia Patients

Dementia patients might have their very own sidekick to help them find their missing items. Think the ability to find medication, glasses, valuables and other items in the near future.

Engineers at the University of Waterloo have developed a game-changing technology that uses robots to assist individuals with dementia in finding misplaced items. 

With it comes the potential to improve the daily lives of people with cognitive impairments like dementia. It could also be used in the future to help you locate those keys that you keep losing.

Dr. Ali Ayub, a post-doctoral fellow in electrical and computer engineering, states, “A user can be involved not just with a companion robot, but a personalised companion robot that can give them more independence.”

The research team made clever use of AI and a detection algorithm to allow a Fetch mobile manipulator robot to detect, track, and log specific objects.

“With the robot capable of distinguishing one object from another, it can record the time and date objects enter or leave its view”, says ScienceDaily.

New Findings To Slash Data Center Chip Consumption

Researchers have achieved a significant breakthrough in reducing the energy consumption of photonic chips used in data centres and supercomputers. 

Wait. Photonic chips?

Unlike conventional computer chips, photonic chips use photons rather than electrons. They’re a lot faster.

Moving at the speed of light, these chips allow rapid and energy-efficient data transmission. You know, the type that massive data centres need to run tech giants like Facebook, Amazon and Google.

“The issue with photonic chips is that up until now, significant energy has been required to keep their temperature stable and performance high,” says ScienceDaily.

The research team introduced an ultra-energy-efficient method to mitigate the impact of temperature fluctuations that can compromise photonic chip performance.

By utilising gate voltage control, the team demonstrated a remarkable reduction in energy requirements for temperature stabilisation. Surpassing a factor of 1 million. 

This breakthrough is significant as it reduces the reliance on thermal heaters, which consume several milliwatts of electricity per device. And when multiplied by millions of devices, this energy consumption quickly becomes substantial. 

The researchers aim to enable data centres to continue their exponential growth in processing power while using significantly less energy. This is paving the way for more powerful applications driven by machine learning without the guilt of excessive energy usage.

Conducting a Million Microbial Experiments Annually

AI has taken yet another giant leap forward in scientific discovery. This time with the development of an AI system that enables robots to conduct up to 10,000 autonomous experiments per day. 

Dubbed BacterAI, this AI platform has the potential to revolutionise fields such as medicine, agriculture, and environmental science. 

In a recent study published in Nature Microbiology, researchers led by a professor from the University of Michigan utilised BacterAI to map the metabolism of two oral health-associated microbes.

“We know almost nothing about most of the bacteria that influence our health. Understanding how bacteria grow is the first step toward reengineering our microbiome,” said Paul Jensen, U-M assistant professor of biomedical engineering.

BacterAI faced the challenge of determining the amino acid requirements for the growth of Streptococcus gordonii and Streptococcus sanguinis. 

The complexity lays in the fact that the 20 amino acids could yield over a million possible combinations. Through trial and error, BacterAI honed its focus and changed combinations daily based on the previous day’s results. This achieved accurate predictions 90% of the time within just nine days.

This new approach, which allows the AI agent to make mistakes and learn from them, holds great potential for accelerating research in various fields. As Adam Dama, the lead author of the study, explains, “focused applications of AI like our project will accelerate everyday research.” 

With the ability to run thousands of experiments in a day, this AI-driven autonomous experimentation is set to transform scientific discovery.

Prepare Yourself for Another Action-Packed Month Ahead

Every month has a smorgasbord of findings and discoveries in the field of AI and tech.

Don’t miss out on any of the exciting news in the coming month of June!

If you enjoy getting a brief update on AI news – then be sure to check out the rest of our content!

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