DeepMind, a British company owned by Google, may be on the verge of achieving human-level artificial intelligence (AI). Nando de Freitas, a research scientist at DeepMind and machine learning professor at Oxford University, has said'the game is over' in regards to solving the hardest challenges in the race to achieve artificial general intelligence (AGI). AGI refers to a machine or program that has the ability to understand or learn any intellectual task that a human being can, and do so without training. According to De Freitas, the quest for scientists is now scaling up AI programs, such as with more data and computing power, to create an AGI. Earlier this week, DeepMind unveiled a new AI'agent' called Gato that can complete 604 different tasks'across a wide range of environments'. Gato uses a single neural network – a computing system with interconnected nodes that works like nerve cells in the human brain.
In September 2021, scientists Sean Ekins and Fabio Urbina were working on an experiment they had named the "Dr. The Swiss government's Spiez laboratory had asked them to find out what would happen if their AI drug discovery platform, MegaSyn, fell into the wrong hands. In much the way undergraduate chemistry students play with ball-and-stick model sets to learn how different chemical elements interact to form molecular compounds, Ekins and his team at Collaborations Pharmaceuticals used publicly available databases containing the molecular structures and bioactivity data of millions of molecules to teach MegaSyn how to generate new compounds with pharmaceutical potential. The plan was to use it to accelerate the drug discovery process for rare and neglected diseases. The best drugs are ones with high specificity--acting only on desired or targeted cells or neuroreceptors, for instance--and low toxicity to reduce ill effects.
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Artificial intelligence does all kinds of things….genomics Genetic engineering has always been a go-to plot twist in sci-fi movies and TV shows. The idea of genetically mutated humans with superior abilities and unique DNAs still has ripple effects on Marvel fans and box offices. But what if we can alter genes in real life? CRISPR gene editing has been doing that since 2012 (no Wolverine or Magneto though). In 2022, this powerful genetic engineering technique is complemented with artificial intelligence.
A 3D rendering of a protein complex structures predicted from protein sequences by AF2Complex. From the muscle fibers that move us to the enzymes that replicate our DNA, proteins are the molecular machinery that makes life possible. Protein function heavily depends on their three-dimensional structure, and researchers around the world have long endeavored to answer a seemingly simple inquiry to bridge function and form: if you know the building blocks of these molecular machines, can you predict how they are assembled into their functional shape? This question is not so easy to answer. With complex structures dependent on intricate physical interactions, researchers have turned to artificial neural network models – mathematical frameworks that convert complex patterns into numerical representations – to predict and "see" the shape of proteins in 3D.
Whether we realize it or not, most of us deal with artificial intelligence (AI) every day. Each time you do a Google Search or ask Siri a question, you are using AI. The catch, however, is that the intelligence these tools provide is not really intelligent. They don't truly think or understand in the way humans do. Rather, they analyze massive data sets, looking for patterns and correlations.
MIT scientists have developed a machine learning model that proposes new molecules for the drug discovery process, while ensuring the molecules it suggests can actually be synthesized in a laboratory. A new artificial intelligence technique has been developed that only proposes candidate molecules that can actually be produced in a lab. Pharmaceutical companies are using artificial intelligence to streamline the process of discovering new medicines. Machine-learning models can propose new molecules that have specific properties which could fight certain diseases, accomplishing in minutes what might take humans months to achieve manually. But there's a major hurdle that holds these systems back: The models frequently suggest new molecular structures that are difficult or impossible to produce in a laboratory.
A dangerous, new group of synthetic opioids called nitazenes are rapidly spreading across the U.S. LONDON, Ohio – A dangerous, new group of synthetic opioids called "nitazenes" is rapidly spreading across the U.S. In Ohio, the state's Attorney General Dave Yost issued a warning about the prevalence of nitazenes as the Buckeye state saw an increase in the illicit drug. The drug, nicknamed "Frankestein opioids," can be 1.5 to 40 times more potent than fentanyl. It is not approved for medical use anywhere in the world but is currently being made in clandestine labs, according to a bulletin from the Ohio Bureau of Criminal Investigation (BCI). At BCI, forensic experts are sounding the alarm after tracking a year-over-year increase in nitazenes. In the first quarter of 2022, BCI reported 143 nitazene cases in Ohio, up from 27 cases in the same quarter of 2021.
This week iSono Health announced FDA clearance of the company's ATUSA System for breast imaging. This is world's first AI-driven portable and automated 3D breast ultrasound scanner. In just 2 minutes, the ATUSA system automatically scans the entire breast volume, independent of operator expertise, and offers 3D visualization of the breast tissue. The ATUSA system is designed from the ground up to seamlessly integrate with advanced machine learning models that will give physicians a comprehensive set of tools for decision making and patient management. This is the first of several intended FDA submissions for the company.
Elon Musk's Neuralink rival Synchron has begun human trials of its brain implant that lets the wearer control a computer using thought alone. The firm's Stentrode brain implant, about the size of a paperclip, will be implanted in six patients in New York and Pittsburgh who have severe paralysis. Stentrode will let patients control digital devices just by thinking and give them back the ability to perform daily tasks, including texting, emailing and shopping online. Although the implant has already been implanted and tested in Australian patients, the new clinical trial marks the first time it will be tested in the US. If successful, the Stentrode brain implant could be sold as a commercial product aimed at paralysis patients to regain their independence and quality of life.