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Category: robotics/AI – Page 2,074

First Accuray CyberKnife M6 System Installed in Missouri

February 27, 2020 — Accuray Incorporated announced that Mercy Hospital St. Louis continues to demonstrate its commitment to improving patient outcomes with the installation of the first CyberKnife M6 System in Missouri at their state-of-the-art David C. Pratt Cancer Center. The next-generation CyberKnife System has been shown to deliver precise stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) treatments with ease, making it possible for the clinical team to expand access to one of the most advanced methods for administering radiation to more cancer patients.

SRS and SBRT are non-invasive forms of radiation therapy that use high doses of very targeted radiation to destroy tumors, in just a few treatment sessions (1 to 5). SRS is commonly used to treat conditions within the brain and spine, while SBRT is used for those tumors located outside these areas. The CyberKnife M6 System is equipped with sophisticated functionality that will streamline the creation of personalized treatment plans and reduce the time to deliver radiation treatments, enabling the Mercy St. Louis team to offer precision SRS and SBRT treatments to more patients each day.

The Mercy Hospital St. Louis team uses the most advanced radiotherapy technology to design and deliver an individualized treatment plan designed to help cancer patients take control of their disease and resume their lives. The hospital is part of the Mercy system, named one of the top five large U.S. health systems from 2016 to 2019 by IBM Watson Health. Mercy announced in 2018 that it intended to work with Accuray to enhance cancer care through advanced life-saving technology, including the CyberKnife System that was recently installed as well as Accuray Radixact Systems that will be installed at other Mercy hospitals.

DeepMind releases Acme, a distributed framework for reinforcement learning algorithm development

DeepMind this week released Acme, a framework intended to simplify the development of reinforcement learning algorithms by enabling AI-driven agents to run at various scales of execution. According to the engineers and researchers behind Acme, who coauthored a technical paper on the work, it can be used to create agents with greater parallelization than in previous approaches.

Reinforcement learning involves agents that interact with an environment to generate their own training data, and it’s led to breakthroughs in fields from video games and robotics to self-driving robo-taxis. Recent advances are partly attributable to increases in the amount of training data used, which has motivated the design of systems where agents interact with instances of an environment to quickly accumulate experience. This scaling from single-process prototypes of algorithms to distributed systems often requires a reimplementation of the agents in question, DeepMind asserts, which is where the Acme framework comes in.

How AI Will Make Drug Discovery Low-Cost, Ultra-Fast, and Personalized

Life-saving Ai

If you had to guess how long it takes for a drug to go from an idea to your pharmacy, what would you guess? Three years? Five years? How about the cost? $30 million? $100 million?

Well, here’s the sobering truth: 90 percent of all drug possibilities fail. The few that do succeed take an average of 10 years to reach the market and cost anywhere from $2.5 billion to $12 billion to get there.

But what if we could generate novel molecules to target any disease, overnight, ready for clinical trials? Imagine leveraging machine learning to accomplish with 50 people what the pharmaceutical industry can barely do with an army of 5,000.

First boat to make its own hydrogen fuel from seawater

Solar power, hydrogen fuel from seawater, automatic wingsails, a 6 year journey.

The Energy Observer set sail on a six-year world tour in 2017, testing new technologies, from onboard hydrogen electrolysis to fully-automated sails. It’s hoped the rugged ocean environment will prove the techs’ durability and usefulness at home.

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AI Is All the Rage. So Why Aren’t More Businesses Using It?

For a lot of smaller companies, AI isn’t part of the picture—not yet, at least. “Big companies are adopting,” says Brynjolfsson, “but most companies in America—Joe’s pizzeria, the dry cleaner, the little manufacturing company—they are just not there yet.”

A big study by the US Census Bureau finds that only about 9 percent of firms employ tools like machine learning or voice recognition—for now.

How AI is uncovering the ‘dark matter of nutrition’

The COVID-19 pandemic didn’t just transform how we work and communicate. It also accelerated the need for more proactive health measures for chronic health problems tied to diet. Such problems have emerged as a top risk factor for coronavirus and people with poor metabolic health accounted for half of COVID-19 hospitalizations in some regions around the world. The resulting high numbers led the authors of a report in The Lancet to issue a call for more resources to tackle metabolic health to avoid needless deaths.

Thankfully, new tools have been developed to offer comprehensive understanding of nutrition. This expertise and technology won’t just help us tackle metabolic health – it could help us finally fully realize the power of plants to improve health and wellness outcomes.

Tesla Autopilot Accidents: 1 out of 4,530,000 Miles; US Average: 1 out of 479,000 Miles

Tesla has released its quarterly “Tesla Vehicle Safety Report.” One of the top reasons — if not the #1 reason — I bought a Tesla Model 3 last was because of its record-setting safety rating, so I’m always interested in seeing new stats on this topic.

The second quarter of 2020 saw a slightly worse result for Tesla than the first quarter in terms of accidents per million miles driven with Tesla Autopilot engaged (see graph below), but keep in mind that the first quarter had a record result. Additionally, the difference was so small that it was probably not statistically significant. On the other hand, Tesla’s Q2 figure was far better than the US average — about 10 times better with Autopilot engaged.

Surprisingly Recent Galaxy Discovered Using Machine Learning – May Be the Last Generation Galaxy in the Long Cosmic History

Breaking the lowest oxygen abundance record.

New results achieved by combining big data captured by the Subaru Telescope and the power of machine learning have discovered a galaxy with an extremely low oxygen abundance of 1.6% solar abundance, breaking the previous record of the lowest oxygen abundance. The measured oxygen abundance suggests that most of the stars in this galaxy formed very recently.

To understand galaxy evolution, astronomers need to study galaxies in various stages of formation and evolution. Most of the galaxies in the modern Universe are mature galaxies, but standard cosmology predicts that there may still be a few galaxies in the early formation stage in the modern Universe. Because these early-stage galaxies are rare, an international research team searched for them in wide-field imaging data taken with the Subaru Telescope. “To find the very faint, rare galaxies, deep, wide-field data taken with the Subaru Telescope was indispensable,” emphasizes Dr. Takashi Kojima, the leader of the team.

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