Logy.ai Introduces India’s First AI-based Cataract Screening Solution with Sharp Sight Eye Hospitals

Sharp Sight Eye Hospitals introduces an AI-based cataract screening solution available on Whatsapp with Logy.ai technology, which yields an accuracy of 92%. 

By Disha Chopra

Logy.ai, in collaboration with Sharp Sight Eye Hospitals, New Delhi, has introduced AI as a screening solution to identify cataracts with an accuracy of 92%. The innovation presents a simple chatbot on WhatsApp and would not require any additional application. The screening can be done in rural areas. 

Logy.ai is an intelligent care service provider aiming to bring AI with a user-friendly interface. In recent developments, the company has helped Sharp Sight Eye Hospitals to solidify its position as a leading eye care provider that uses AI for health screening. The latter is an established eye care provider with over 10 lakh successful procedures and surgeries in its 14 facilities in North and East India centers. 

Priyanjit Ghosh, Co-founder, and CEO, of Logy.ai, expressed that Sharp Sight Eye Hospitals is a proactive partner with the firm. Their partnership synergizes with Logy.ai’s vision of new-era technologies like AI to promote health screening. The collaboration aims to build top-of-the-line AI products in the healthcare domain and bridge the gap between technology and medicine. 

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We Asked an AI to Draw a Self-Portrait

Pay no attention to the machine learning algorithm behind the curtain.

By Janus Rose

DALL-E, the AI system that generates images from text prompts, has captured the internet’s imagination over the past few months. Literally.

Created by OpenAI, DALL-E is the latest in a series of tools that seem to tap into the internet’s subconscious, using massive datasets of text and images to parse and reproduce human language with uncanny accuracy. The system uses a machine learning model with billions of individual parameters to illustrate whatever phrases you feed into it, resulting in bizarre and often shockingly realistic renderings—though oftentimes with predictably racist and sexist tropes.

But while access to DALL-E is currently only being offered to a select list of artists and researchers, open source AI systems that attempt to replicate OpenAI’s model have recently sprouted up, allowing anyone to try their hand at human-machine artistic collaboration.

One model in particular, called DALL-E Mini, has practically achieved meme status over the past week. Hosted on the AI repository HuggingFace, the demo’s massive volume of users has caused long delays to complete requests, as social feeds fill with images generated from all kinds of absurd prompts. (“Gender reveal 9/11” and “Aileen Wuornos on Drag Race” are among the many deranged highlights)

Given how so many humans are now collaborating with AI models to make art, I felt it was only fair to ask the AI to reveal itself as a self-portrait. 

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Scientists in China have successfully cloned pigs using only AI in a world first

By  Rupendra Brahambhatt

And without any human involvement.

A team of researchers from the College of Artificial Intelligence at Nankai University in China has developed a fully automated method to create pig clones. For the first time, seven healthy cloned piglets were born to a surrogate mother in March without any human intervention using the same method. 

China is currently the biggest pork producer and consumer in the world. The pig population in the country stands at over 400 million, and pork consumption is between 30 and 35 kg per capita. A large share of the meat eaten in China is pork, and the available stock in the country is never enough to meet the demand. This is why China has to import millions of tons of expensive pig meat every year; even in 2021, the country purchased 3.31 million metric tonnes of pork.

Liu Yaowei, one of the researchers at Nankai University, believes that their AI-powered automated pig cloning method can significantly increase China’s pig population and make the country completely self-sufficient in pork production.

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Artificial ‘inventors’ are pushing patent law to its limits

It was the veritable search for a needle in a haystack. With drug-resistant bacteria on the rise, researchers at MIT were sifting through a database of more than 100 million molecules to identify a few that might have antibacterial properties. 

Fortunately, the search proved successful. But it wasn’t a human who found the promising molecules. It was a machine learning program. 

One compound has been patented under the name Halicin in homage to HAL, the artificial intelligence (AI) in Arthur C Clarke’s classic 2001: A Space Odyssey. Halicin works differently from existing antibiotics, disrupting the bacteria’s ability to access energy, and researchers hope bacteria may struggle to develop resistance to it. 

Halicin might be the first antibiotic discovered using AI, but AI programs have played an important role in other patented inventions from electrical circuits, through meta-materials and drugs, to consumer products such as toothbrushes. As we argue in a recent article in Nature, society urgently needs to consider the impact of AI on the innovation system, particularly on laws regarding intellectual property and patents.

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Revolut founder set to launch venture capital fund powered by artificial intelligence

By Lucy Harley-McKeown

The new venture — dubbed QuantumLight Capital — will be worth around $200 million, with funds supplied by Storonsky and other investors, Forbes reported on Tuesday. 

“We are built as a technology company by a team of tech unicorn founders, quant traders, AI scientists and engineers,” the QuantumLight website states. The fund will identify investment opportunities using a machine called Aleph as its “proprietary quantitative decision engine.” 

According to Forbes, QuantumLight will be focused mainly on Series B and Series C rounds, based on software which eliminates “human judgement.” Storonsky argues that the model is designed to eliminate the clubby world of venture capital, where decisions are made through a crowd mentality. 

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Orca AI-driven Autonomous Ship Sails 800 Km In Tokyo Bay Without Human Assistance

Orca AI specialises in developing software, especially for maritime vessels, and claims to be working toward reducing human-caused errors.

By Harsh Vardhan 

A 749 gross-ton autonomous vessel successfully completed a 40-hour-long journey without any human assistance. Touted as the world’s first autonomous commercial cargo ship, it was equipped with Orca AI’s technology which helped it travel through the congested waters of Tokyo Bay. Interestingly, the vessel was able to avoid hundreds of collisions along its way and completed 99% of its journey alone, Electrek reported. 

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UAH collaboration creates self-learning AI platform to discover new drugs

A UAH team is applying self-learning artificial intelligence and big data analytics to discover new drugs.

Newswise — HUNTSVILLE, Ala. (May 4, 2022) – A cross-college collaboration at The University of Alabama in Huntsville (UAH) has developed a self-learning artificial intelligence (AI) platform that uses big data analytics to discover how new pharmaceutical drugs and various molecules work inside living cells.

The cutting-edge research at UAH, a part of the University of Alabama System, involves Dr. Jerome Baudry, a molecular biophysicist, the Mrs. Pei-Ling Chan Chair in the Department of Biological Sciences and director of the Baudry Lab; Dr. Vineetha Menon, an assistant professor in the Department of Computer Science and the director of the Big Data Analytics Lab; computer science doctoral student Shivangi Gupta, the lead author of a paper on the research; and engineering doctoral student Armin Ahmadi, who is conducting his doctoral research in the Baudry Lab.

Supported by UAH’s Office of Technology Commercialization, the scientists are developing their research into intellectual property for industrial applications in drug discovery.

“This is a strong, integrated collaboration and we all bring our own expertise, but the main novelty in this work is in machine learning and data mining, and the lead on the overall project is Dr. Menon, who is an internationally recognized expert in these areas,” says Dr. Baudry.

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Waste plastic broken down not in centuries but in days by an AI-engineered enzyme

Breaking up is hard to do.

That’s certainly true for common plastics like polyethylene terephthalate (PET).  A water bottle made of a thin film of PET (perhaps half a millimeter thick) takes about 450 years to degrade.  Along the way it will exist as microplastics, which are so pervasive they are even turning up in living people’s lung tissue, as we saw for the first time just a month ago.  And even those kinds of numbers are guesstimates because many studies don’t last long enough to see any appreciable degradation of PET at all.

A lot of efforts to produce biodegradable and bioresorbable plastics are making good progress, and that’s great for the future, but what about the mountains of plastic that already exist and that we keep on generating?  In the U.S., the landfill rate for discarded plastics is still about 75%!  We have a lot of work to do.

Good thing Hal Alper’s chemical engineering lab at the University of Texas is on the job.  In the April 27 issue of Nature, they report on an enzyme they developed called FAST-PETase.  Designed with the help of artificial intelligence, it degrades untreated postconsumer PET not in centuries, but in days.  And this can be done at temperatures of 50°C and below, where many types of bacteria can thrive.  See where this is going?

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John Deere is slowly becoming one of the world’s most important AI companies

Nothing runs (autonomously) like a Deere

By Tristan Greene

John Deere has been in business for nearly 200 years. For those in the agriculture industry, the company that makes green tractors is as well-known as Santa Claus, McDonald’s, or John Wayne.

Heck, even city folk who’ve never seen a tractor that wasn’t on a television screen know John Deere. The company’s so popular even celebrities such as Ashton Kutcher and George Clooney have been known to rock a Deere hat.

What most outsiders don’t know is that John Deere’s not so much a farming vehicle manufacturer these days as it is an agricultural technology company. And, judging by how things are going in 2022, we’re predicting it’ll be a full-on artificial intelligence company within the next 15 years.

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AI Speeds Precision Medicine for Parkinson’s Disease

Robotics combined with AI machine learning spots Parkinson’s disease signatures.

By Vanessa Lancaster

KEY POINTS

  • Over 10 million people worldwide live with Parkinson’s disease, including nearly a million Americans.
  • A new study uses AI deep learning that finds cellular disease signatures to help accelerate the discovery of novel therapeutics for Parkinson’s. 
  • This unique AI deep learning platform solution is not limited to Parkinson’s disease. It can be repurposed for other disease signatures.

Artificial intelligence (AI), machine learning, and robotics are accelerating precision medicine for neurodegenerative diseases and brain disorders.

A new study published in Nature Communications reveals a high-throughput screening platform using AI deep learning that finds cellular disease signatures to help accelerate the discovery of novel therapeutics for Parkinson’s disease (PD).

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AI THAT BUILDS AI: SELF-CREATION TECHNOLOGY IS TAKING A NEW SHAPE

Deep neural networks, a type of Artificial Intelligence began outperforming standard algorithms 10 years ago.

by Madhurjya Chowdhury

The majority of artificial intelligence (AI) is a game of numbers. Deep neural networks, a type of AI that learns to recognize patterns in data, began outperforming standard algorithms 10 years ago because we ultimately had enough data and processing capabilities to fully utilize them.

Today’s neural nets are even more data and power-hungry. Training them necessitates fine-tuning the values of millions, if not billions, of parameters that define these networks and represent the strength of interconnections between artificial neurons. The goal is to obtain near-ideal settings for them, a process called optimization, but teaching the networks to get there is difficult.

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Researchers develop new AI form that can adapt to perform tasks in changeable environments

Robot Tiego is ready to stack cubes.

by Sandra Tavakoli and Karin Wik,  Chalmers University of Technology

Can robots adapt their own working methods to solve complex tasks? Researchers at Chalmers University of Technology, Sweden, have developed a new form of AI, which, by observing human behavior, can adapt to perform its tasks in a changeable environment. The hope is that robots that can be flexible in this way will be able to work alongside humans to a much greater degree.

“Robots that work in human environments need to be adaptable to the fact that humans are unique, and that we might all solve the same task in a different way. An important area in robot development, therefore, is to teach robots how to work alongside humans in dynamic environments,” says Maximilian Diehl, Doctoral Student at the Department of Electrical Engineering at Chalmers University of Technology and main researcher behind the project.

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