Automatic license plate recognition (ALPR) and vehicle make and model recognition underpin intelligent transportation systems, supporting law enforcement, toll collection, and post-incident investigation. Applying these methods to videos captured by handheld smartphones or non-static vehicle-mounted cameras presents unique challenges compared to fixed installations, including frequent camera motion, varying viewpoints, occlusions, and unknown road geometry. Traditional ALPR solutions, dependent on specialized hardware and handcrafted OCR pipelines, often degrade under these conditions. Recent advances in large vision-language models (VLMs) enable direct recognition of textual and semantic attributes from arbitrary imagery. This study evaluates the potential of VLMs for ALPR and makes and models recognition using monocular videos captured with handheld smartphones and non-static mounted cameras. The proposed license plate recognition pipeline filters to sharp frames, then sends a multimodal prompt to a VLM using several prompt strategies. Make and model recognition pipeline runs the same VLM with a revised prompt and an optional self-reflection module. In the self-reflection module, the model contrasts the query image with a reference from a 134-class dataset, correcting mismatches. Experiments on a smartphone dataset collected on the campus of the University of Texas at Austin, achieve top-1 accuracies of 91.67% for ALPR and 66.67% for make and model recognition. On the public UFPR-ALPR dataset, the approach attains 83.05% and 61.07%, respectively. The self-reflection module further improves results by 5.72% on average for make and model recognition. These findings demonstrate that VLMs provide a cost-effective solution for scalable, in-motion traffic video analysis.

For the doctors of the future, and their creators, the re-invention of the healthcare system must begin with those working on the frontline. WIRED and HP present ten innovators developing the artificially intelligent, entrepreneurial, and on-demand doctors who are set to transform the delivery of healthcare. Subjectivity is the last quality you want in medical diagnosis, but with complex noisy scans an objective conclusion can be hard to come by. At the University of Copenhagen's department of computer science, Mads Nielsen is working on the use of machine learning to provide automatic, accurate and quantitive analyses of common medical imagery. Applications including screening for breast cancer risk in mammograms, Alzheimer's development in brain MRI scans, and arthritis in hand and knee MRI images, are being developed through his spin-out company, Biomediq.

Bioengineering of human beings have been tried throughout the world by the Military Industrial Complex, secret labs, governments, and corporations. I unclassified this information with relation to China on Aug 24th, 2019 with the publication of AI, Trump, China and the Weaponization with Robotics with 5G, and the last 2 books, Artificial Intelligence Dangers to Humanity and The Great Reset: How Big Tech Elites and the World's People Can Be Enslaved by China CCP or A.I.. In December, the Pentagon verified The AI Organization's findings with serius concern, as it pertains to the CCP and China. Imagine a future, where gen edited babies raised to become Super Soldiers meant for military dominance and assassination's of public figures. This can be a reality in numerous intricate ways. As I see it, the Chinese regime threatens the lives of the world's people with AI, bioweapons, persecution, soft power, social engineering, and enslavement by using the Art of War.

President Trump states after Davos " Elon Musk is the Thomas Edison of our time, he needs be protected". Elon is needed by the military and U.S against China's advancements to the free world. Cyrus A. Parsa, wishes the best for him, the U.S and the worlds people. Yet, he must cut off all ties with China for the worlds safety, and make sure his advancements in AI technology do not endanger to the worlds people or the worlds governments beyond Artificial Narrow Intelligence.

If you're a parent with young kids, you probably know how arduous it can be to screen a babysitter. And among those who have hired one, a whopping 62 percent didn't bother to check their references. That spurred Sal Parsa and Joel Simonoff, the cofounders of Berkeley startup Predictim, to develop a no-frills solution that taps artificial intelligence (AI) to generate personality assessments from digital footprints. The eponymous Predictim platform, which launches today, uses natural language processing (NLP) and computer vision algorithms to sift through social media posts -- including tweets, Facebook posts, and Instagram photos -- for warning signs. "The current background checks parents generally use don't uncover everything that is available about a person. Interviews can't give a complete picture," Parsa said.

Digital healthcare specialist Babylon has announced plans to invest $100 million to create a multi-disciplinary team dedicated to building next-generation, AI-powered healthcare technologies. The move forms part of a long-term product and service strategy to apply AI to chronic disease management. It builds on recent partnerships with the likes of Tencent, Samsung, Bupa, Prudential, The Gates Foundation, and TELUS. As Babylon scales its operations internationally, it is increasing its focus on chronic conditions – which affect half the US population. Twenty-five percent of the populace in developed countries suffer from mental health issues, while diabetes and anti-obesity treatments cost the UK's NHS an estimated £10 billion and £5 billion each year, respectively.

British medical startup Babylon Health will invest $100 million in hiring more than 500 researchers, scientists, and engineers over the next year to develop the use of artificial intelligence in healthcare. Chief executive Ali Parsa said this would bring Babylon's current team to more than 1,000 staff, and that the company would eventually move into new headquarters in London over the next 18 months to house the additional recruits. The firm is currently headquartered in Kensington, London, and plans to take over the rest of the offices in its building. The artificial intelligence research will build on software that Babylon showed off in late June. The company claimed at the time that its AI could assess common conditions more accurately than doctors.

There are about 10,000 known human diseases, yet human doctors are only able to recall a fraction of them at any given moment. As many as 40,500 patients die annually in an ICU in the U.S. as a result of misdiagnosis, according to a 2012 Johns Hopkins study. British entrepreneur Ali Parsa believes that artificial intelligence can help doctors avoid these mistakes. Parsa is the founder and CEO of Babylon, a U.K.-based subscription health service that plans to launch an AI-based app designed to improve doctors' hit rate. Users will report the symptoms of their illness to the app, which will check them against a database of diseases using speech recognition.

Earlier this year a report by the King's Fund highlighted the tremendous difficulties startups have in scaling up their technologies in the healthcare sector. It cited things such as a lack of appetite for change and insufficient resources to scale up successful pilots as key factors holding back innovation in the sector. Such conclusions are not new however, with many shared with previous reports on the topic. For instance, the King's Fund report follows on from the Accelerated Access Review, which was designed to speed up the introduction of technologies and innovations into the NHS. Many of the recommendations from that are shared with the King's Fund report, as they are with another report from the Health Foundation.

Prudential Asia, a business unit of British insurer Prudential plc., has signed a licensing deal with digital health startup Babylon Health to exclusively use its AI-powered software for its own apps across 12 countries in Asia. Prudential is paying approximately $100 million over the course of several years, according to sources close to the deal, to access proprietary software that includes an inference engine, simulation software and a medical-knowledge graph that over time aims to replicate and automate consultations with human doctors. Babylon declined to comment on the deal pricing, and spokespeople for Prudential Asia could not be reached for comment on pricing. Babylon Health is best known for providing a virtual-doctor service in the U.K., where more than 26,000 NHS patients in London can get appointments with doctors via video calls and thousands more use its private service for $80 a year. Babylon won't provide remote doctors to Prudential; it'll instead provide the software that powers the medical chatbot on its app.