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Omni Unchanged exemplifies the 'Speak Less, Say More' philosophy in Rad AI Omni Reporting, empowering radiologists to tackle complex exams more efficiently, decreasing stress and repetitive workload.

SAN FRANCISCO, Nov. 26, 2023 /PRNewswire/ -- Rad AI, the fastest-growing radiologist-led AI company and winner of AuntMinnie's Best New Radiology Software award for 2023, has announced the launch of its latest groundbreaking feature in Omni Reporting: Omni Unchanged. This remarkable feature is set to revolutionize radiology reporting by enabling radiologists to dictate complex follow-up exams up to 50% faster, using up to 90% fewer words. Rad AI previously announced several initial features of Omni Reporting at its Launch Day event in late September, which has already sparked significant interest within the radiology community.

Omni Unchanged extracts stable and unchanged findings from prior reports and inserts them into the proper location within the radiologist's existing preferred report template. Hence, radiologists only need to dictate new or updated findings. For exams that haven't changed, radiologists only have to dictate "Omni Unchanged" even if the exam has multiple complex findings. These features mark a significant step in Rad AI's mission to streamline radiology reporting processes, enabling radiologists to operate at the top of their licenses with greater efficiency.

Built for speed, performance, and accuracy, Omni Reporting helps radiologists create more of the report automatically.

"Having been a practicing radiologist and user of speech recognition for radiology reporting for over two decades, I am excited to lead this transformative project. With Omni Reporting, we aim to help radiologists refocus on their crucial task of analyzing imaging exams and providing expert interpretation. Omni Unchanged takes Rad AI's commitment to automating repetitive tasks, reducing cognitive stress, and enhancing radiologist efficiency to a whole new level," said William Boonn MD, Chief Medical Officer of Rad AI.

Omni Reporting builds on Rad AI's leadership in generative AI and track record of performant cloud-native modern radiology software to enable a "Speak Less, Say More" experience for radiologists, saving radiologists time and reducing cognitive load. Omni Reporting was designed to enable a seamless transition from other reporting products. Personal and system templates can be easily imported from your existing reporting system, with full support for your current microphone setup and hardware, lowering the barrier to entry with minimal need for training.

Built from the ground up for speed, performance, and accuracy, Omni Reporting helps radiologists create more of the report automatically in the radiologist's style and language while generating individually customized impressions using Omni Impressions. Omni Reporting's open architecture enables seamless integration with imaging AI vendors and PACS companies and allows radiology practices to develop and manage their own real-time analytics.

John Paulett, Director of Engineering at Rad AI, and the chief architect of Omni Reporting added: "The development of Omni Reporting from the ground up with modern architecture and the latest in generative AI, sets Omni Reporting as the future-proof platform for radiology. We focus on speed, ease of use, and interoperability, enabling seamless adoption into existing IT frameworks and future AI applications."

Rad AI's introduction of Omni Unchanged at RSNA 2023 continues its legacy of innovation in radiology, following the success of its previous solutions, including Rad AI Omni Impressions, Continuity, and Nexus. Omni Unchanged is expected to redefine the standard for radiology reporting software, reinforcing Rad AI's position as a leader in radiology AI solutions.

"Rad AI is uniquely positioned to transform the radiology reporting landscape," said CEO Doktor Gurson. "Having been the pioneer in introducing large language models (LLMs) to radiology in 2018 with our Rad AI Omni Impression solution, we're now expanding the use of our technology across various facets of the radiology reporting workflow and are harnessing the power of generative AI in truly novel and transformative ways to empower radiologists. By ushering in the next generation of radiology reporting and taking radiology reporting from stagnation to innovation, we will improve the daily work and lives of radiologists and patients across the globe."

Those interested in partnering with Rad AI for Omni Reporting should book a demo for a remaining slot at radai.com/rsna2023. For any questions, contact [emailprotected].

About Rad AI

Rad AI is the fastest-growing radiologist-led AI company and the pioneer in generative AI in radiology since 2018, having now saved radiologists nearly one billion fewer words dictated. In addition to being named AuntMinnie's "Best New Radiology Software" in 2023 for Omni Reporting and "Best New Radiology Vendor" in 2021, CB Insights listed Rad AI as one of the most innovative digital health startups and one of the world's most promising private AI companies in its rankings.

Founded by the youngest radiologist in U.S. history, Rad AI is known for the first and most successful generative AI solution in radiology. Since then, Rad AI has seen rapid adoption of its AI platform, which is already in use at 8 of the 10 largest private radiology practices in the US and trusted by thousands of radiologists. Rad AI uses state-of-the-art machine learning to streamline repetitive tasks for radiologists and automate workflow for health systems, which yields substantial time savings, alleviates burnout, and creates more time to focus on patient care.

Learn more about Rad AI at http://www.radai.com or on Twitter @radai.

SOURCE Rad AI

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Rad AI Unveils Omni Unchanged, a Revolutionary Addition to Omni ... - PR Newswire

Nio, one of Chinas top three builders of premium electric vehicles (EV), aims to reduce its workforce by a third by 2027 as it rapidly replaces them with robots.

Earlier this month, the company said it had cut 10 per cent of its workforce to boost efficiency and stay competitive.

We want to resort to AI technologies to largely reduce reliance on skilled workers and technicians, and hence save more labour costs, he said on Friday. If 80 per cent of our decisions [in manufacturing] can be made by AI, it will enable us to reduce 50 per cent of our managerial positions in 2025.

Industrial robots could help the company cut the use of workers on the production lines by 30 per cent between 2025 and 2027, he added.

Nio had a workforce of about 7,000 at the end of 2022, according to data from corporate registry website Qichacha.

Nio envisions full automation, or a labour-free system, at its manufacturing sites in future, banking on advanced AI and robotic technologies, Ji said. He, however, admitted it was difficult to give a time frame.

02:48

China World Robot Expo 2023: Your next bartender could be a humanoid

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Nio delivered 126,067 vehicles in the first 10 months of 2023, up 36.3 per cent year on year. Its president Qin Lihong said in a speech during the Guangzhou Auto Show on November 17 that 40 per cent year-on-year sales growth was not fast enough to reflect the companys design and manufacturing strength.

The carmaker operates two plants, both in Hefei, capital of eastern Anhui province. The first factory has an annual production capacity of 150,000 units on one shift, while the second is capable of building 300,000 vehicles annually, also on a single shift. A single shift normally requires 1,000 workers.

Nio already has a big production capacity and its manufacturing technique is advanced enough to support high growth, said Chen Jinzhu, CEO of consultancy Shanghai Mingliang Auto Service. The company needs to design and produce more vehicles that can appeal to more Chinese drivers to bolster sales.

02:21

Japan start-up develops Gundam-like robot with US$2.7 million price tag

Japan start-up develops Gundam-like robot with US$2.7 million price tag

At the second plant near Hefei Xinqiao airport, 756 robots are used to achieve 100 per cent automation in one of the manufacturing processes.

Nio aims to turn the factory into the worlds smartest with advanced equipment, flexible processes and efficient supply-chain management, Ji said.

Nios rival, Guangzhou-based Xpeng, said in April that it would fine-tune its designs and improve efficiency next year, hoping to slash costs by 25 per cent to stay ahead of the competition.

The efficiency drive and cost-cutting programme would put unprofitable Xpeng on the road to generate positive cash flow by 2025, the carmakers president Brian Gu said.

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Chinese EV maker Nio sees AI, robots replacing 30% of workforce by 2027 - South China Morning Post

Anthony Levandowski was cleared by Donald Trump of charges relating to the theft of technology secrets from Google. Justin Sullivan / Getty

Anthony Levandowski, a pioneer of self-driving cars and controversial Silicon Valley figure, announced the return of his AI-dedicated church in an episode of Bloomberg's AI IRL podcast.

Levandowski started his "Way of the Future" church in 2015 while he was working as an engineer on Google's self-driving project Waymo.

While the original church was shut a few years later, Levandowski's new venture already has "a couple thousand people" who are trying to build a "spiritual connection" with AI, he said, per Bloomberg.

"Here we're actually creating things that can see everything, be everywhere, know everything, and maybe help us and guide us in a way that normally you would call God," Levandowski said, adding that his aim was to help people gain a deeper understanding of AI and allow more people to have a say in how the technology is used.

"How does a person in rural America relate to this? What does this mean for their job?" he said. "Way of the Future is a mechanism for them to understand and participate and shape the public discourse as to how we think technology should be built to improve you."

Levandowski's church first came under the spotlight in 2017 when he became embroiled in a high-profile court case after he was accused of stealing trade secrets.

Levandowski later pleaded guilty and was sentenced to 18 months in prison. The engineer was pardoned in 2021 by the outgoing president at the time, Donald Trump.

Levandowski's official pardon said he had "paid a significant price for his actions and plans to devote his talents to advance the public good."

The former Googler is now the CEO of Pollen Mobile, a decentralized mobile network he founded in 2021.

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Former Google engineer who was pardoned by Donald Trump revives AI church - Business Insider

The fall semester is well underway, and schools across the United States are rushing to implement artificial intelligence (AI) in ways that bring about equity, access, and efficiency for all members of the school community. Take, for instance, Los Angeles Unified School Districts (LAUSD) recent decision to implement Ed.

Ed is an AI chatbot meant to replace school advisors for students with Individual Education Plans (IEPs), who are disproportionately Black. Announced on the heels of a national uproar about teachers being unable to read IEPs due to lack of time, energy, and structural support, Ed might seem to many like a sliver of hopethe silver bullet needed to address thechronic mismanagement of IEPs andongoing disenfranchisement of Black students in the district. But for Black students with IEPs, AI technologies like Ed might be more akin to a nightmare.

Since the pandemic, public schools have seen a proliferation of AI technologies that promise to remediate educational inequality for historically marginalized students. These technologies claim topredict behavior and academic performance,manage classroom engagement,detect and deter cheating, andproactively stop campus-based crimes before they happen. Unfortunately, because anti-Blackness is often baked into the design and implementation of these technologies, they often do more harm than good.

Proctorio, for example, is a popular remote proctoring platform that uses AI to detect perceived behavior abnormalities by test takers in real time. Because the platform employs facial detection systems that fail to recognize Black faces more than half of the time, Black students have an exceedingly hard time completing their exams without triggering the faulty detection systems, which results in locked exams, failing grades, and disciplinary action.

While being falsely flagged by Proctorio mightinduce test-taking anxiety or result in failed courses, the consequences for inadvertently triggeringschool safety technologies are much more devastating. Some of the most popular school safety platforms, like Gaggle and GoGaurdian, have been known to falsely identify discussions about LGBTQ+ identity, race related content, andlanguage used by Black youth as dangerous or in violation of school disciplinary policies. Because many of these platforms aredirectly connected to law enforcement, students that are falsely identified are contacted by police both on campus and in their homes. Considering that Black youth endure the highest rates of discipline, assault, and carceral contact on school grounds and aresix times more likely than their white peers to have fatal encounters with police, the risk of experiencing algorithmic bias can be life threatening.

These examples speak to the dangers of educational technologies designed specifically for safety, conduct, and discipline. But what about education technology (EdTech) intended for learning? Are the threats to student safety, privacy, and academic wellbeing the same?

Unfortunately, the use of educational technologies for purposes other than discipline seems to be the exception, not the rule. Anational study examining the use of EdTech found an overall decrease in the use of the tools for teaching and learning, with over 60 percent of teachers reporting that the software is used to identify disciplinary infractions.

Whats more, Black students and students with IEPs endure significantly higher rates of discipline not only from being disproportionately surveilled by educational technologies, but also from using tools like ChatGPT to make their learning experience more accommodating and accessible. This could include using AI technologies to support executive functioning, access translated or simplified language, or provide alternative learning strategies.

Many of these technologies are more likely to exacerbate educational inequities like racialized gaps in opportunity, school punishment, and surveillance.

To be sure, the stated goals and intentions of educational technologies are laudable, and speak to our collective hopes and dreams for the future of schoolsplaces that are safe, engaging, and equitable for all students regardless of their background. But many of these technologies are more likely to exacerbate educational inequities like racialized gaps in opportunity, school punishment, and surveillance, dashing many of these idealistic hopes.

To confront the disparities wrought by racially-biased AI, schools need a comprehensive approach to EdTech that addresses the harms of algorithmic racism for vulnerable groups. There are severalways to do this.

One possibility is recognizing that EdTech is not neutral. Despite popular belief, educational technologies are not unbiased, objective, or race-neutral, and they do not inherently support the educational success of all students. Oftentimes, racism becomes encoded from the onset of the design process, and can manifest in the data set, the code, the decision making algorithms, and the system outputs.

Another option is fostering critical algorithmic literacy. Incorporating critical AI curriculum into K-12 coursework, offering professional development opportunities for educators, or hosting community events to raise awareness of algorithmic bias are just a few of the ways schools can support bringing students and staff up to speed.

A third avenue is conducting algorithmic equity audits. Each year, the United Statesspends nearly $13 billion on educational technologies, with the LAUSD spending upwards of$227 million on EdTech in the 2020-2021 academic year alone. To avoid a costly mistake, educational stakeholders can work with third-party auditors to identify biases in EdTech programs before launching them.

Regardless of the imagined future that Big Tech companies try to sell us, the current reality of EdTech for marginalized students is troubling and must be reckoned with. For LAUSDthe second largest district in the country and the home of the fourteenth largest school police force in Californiathe time to tackle the potential harms of AI systems like Ed the IEP Chatbot is now.

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AI Technology Threatens Educational Equity for Marginalized Students - Progressive.org