WIRE)--Knightscope, Inc., a developer of advanced physical security technologies focused on enhancing U.S. security operations, today announced the commencement of its offering of up to $40 million of Class A common stock, with shares to be listed immediately following closing on the Nasdaq Global Market ("NASDAQ") under the ticker symbol "KSCP." The offering is for up to 4 million shares priced at $10 per share. BUY SHARES NOW Digital Offering, LLC, will act as the lead managing selling agent and sole bookrunner for the offering. The Offering can be purchased through multiple broker-dealers for a planned selling period of approximately 30 to 45 days, subject to market conditions. Learn how to buy shares in the public listing now at www.knightscope.com. For additional information on Knightscope, the offering and any other related topics, please review the offering circular that can be found here.

According to the Spanish Ministry of Agriculture, Fisheries and Food, the livestock industry accounted for over €20.2 billion of production in the Spanish economy in 2020. Research at the Universitat Oberta de Catalunya (UOC) has confirmed that this figure could significantly improve with the use of new technologies and artificial intelligence, and better control of all the procedures required in production. A UOC industrial doctoral degree from the Network and Information Technologies programme has concluded that incorporating artificial intelligence and applying it with devices, such as monitoring sensors, would optimize the livestock industry's restocking and service planning processes, leading to higher profit and reduced costs. "Other more highly industrialized sectors have been benefiting from Industry 4.0 principles and proposals for years, but the livestock industry still suffers from a low degree of digitization," said David Raba, author of the thesis. He conducted the research INSYLO Technologies S.L., a company specializing in the development of volumetric sensors and environmental quality.

Mindtree, a global technology services and digital transformation company, today announced it has earned the AI and Machine Learning on Microsoft Azure advanced specialization, a validation of a services partner's deep knowledge, extensive experience and proven success in enabling customer adoption of AI and implementing Azure solutions for machine learning life cycle and AI-powered apps. Only partners that meet stringent criteria around customer success and staff skilling, as well as pass a third-party audit of their AI and machine learning technical practices, are able to earn the AI and Machine Learning on Microsoft Azure advanced specialization. As the speed of business accelerates, organizations of every type and size are looking for ways to streamline processes and deliver simpler, faster, and smarter resources to help them keep up. Partners with the AI and Machine Learning on Microsoft Azure advanced specialization can give organizations the tools and knowledge to develop AI solutions on their terms, build AI into their mission-critical applications, and put responsible AI into action. "We are excited to be among Microsoft's first service partners to have earned the AI and Machine Learning on Microsoft Azure advanced specialization," said Radhakrishnan Rajagopalan, Global Head, Customer Success, Data and Intelligence, Mindtree.

ISM001-055 demonstrated highly promising results in multiple preclinical studies including in vitro biological studies, pharmacokinetic and safety studies. The compound significantly improved myofibroblast activation which contributes to the development of fibrosis. ISM001-055's novel target is potentially relevant to a broad range of fibrotic indications. "We are very pleased to see Insilico Medicine's first antifibrotic drug candidate entering into the clinic. We believe this is a significant milestone in the history of AI-powered drug discovery because to our knowledge the drug candidate is the first ever AI-discovered novel molecule based on an AI-discovered novel target. We have leveraged our end-to-end AI-powered drug discovery platform, including the usage of generative biology and generative chemistry, to discover novel biological targets and generate novel molecules with drug-like properties. ISM001-055 is the first such compound to enter the clinic, and we expect more to come in the near future," said Feng Ren, Ph.D., CSO of Insilico Medicine.

Orchestration--of AI and of workflow--offers a new way to help imaging organizations improve radiologists' reading experience while significantly reducing the impact on IT IBM (NYSE: IBM) Watson Health is introducing a new AI orchestration offering to help imaging organizations experience the benefits of having AI applications work seamlessly together. IBM Watson Health will officially launch IBM Imaging AI Orchestrator at the Radiological Society of North America (RSNA) 2021 Annual Meeting in Chicago this week. In addition, IBM is announcing IBM Imaging Workflow Orchestrator with Watson, a new solution that modernizes the radiologist's reading experience while reducing the demands on IT and imaging system administrators. "We recognize that when it comes to applying AI in imaging, it's hard to go it alone," said David Gruen, MD, MBA, FACR, Chief Medical Officer, Imaging, Watson Health. "Because each AI application is developed in a unique way with a specific purpose, it can be challenging for organizations to review and assess each one, and then to deploy them in a way that's beneficial to radiologists and their patients. That's why, with the rapid proliferation of approved algorithms, staffing shortages, and complexity of disease, the IBM Imaging AI Orchestrator could not come at a better time."

Technology investment company and incubator Red Cell Partners announced today the launch of Zephyr AI, a company that leverages large data sets to inform both clinical care and the development of new targeted precision therapies. The management team of the new company consists of CEO Yisroel Brumer, formerly of the office of the Secretary of Defense; Executive Chairman Grant Verstandig, who most recently served Chief Digital Officer at UnitedHealth Group; and Chief Technology Officer Jeff Sherman, who was the machine learning architect at Rally Health, which was acquired in 2017 by UnitedHealth's Optum unit. According to a press release announcing its launch, Zephyr AI will look to improve patient outcomes while lowering costs by integrating "artificial intelligence with extensive datasets to upend traditional'guess and test' drug development and personalized medicine processes to unearth novel therapeutics, new applications for existing therapeutics, and advanced biomarkers for individualized treatments." The potential new company gave a hint at its direction earlier in the year via the publication of two papers by the founders in the journal Oncogene that detailed the company's technology and it's performance. "These findings demonstrate that Zephyr AI can already identify novel-use cases for existing therapeutics in cancer," company CTO Sherman.

The earliest clinical decision support systems date back to the 1960s, when pharmacists used automated technology to check patient allergies, research dosages, and check for drug-to-drug interactions.(1) Now, according to recent estimates, up to 74 percent of healthcare provider organizations use clinical decision support (CDS) technology.(2) These systems harness the power of artificial intelligence (AI) to help provide clinicians, staff members, patients, and others with person-specific health information. In New Jersey, a CDS system known as Clover Assistant is taking hold as an invaluable resource for physicians--the platform provides clinicians with patient-specific information that is relevant to the visit, as well as providing actionable insights to help improve long-term outcomes and guide preventative care.(3) But there is still the problem of fragmentation. Stuart Long, CEO of InfoBionic, a leading digital cardiac health company, says, "CDS systems are great for helping physicians arrive at appropriate and timely clinical decisions regarding many aspects of patient care.

Philips' industry-first Tube for Life guarantee minimizes lifetime operating costs and provides reliability to help ensure efficient operation Amsterdam, the Netherlands and Chicago, USA – Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, today announced new additions to its CT imaging portfolio at the Radiological Society of North America (RSNA) annual meeting (November 28 – December 2, Chicago, USA). The new CT 5100 – Incisive – features CT Smart Workflow [1], a comprehensive suite of artificial intelligence* (AI) enabled capabilities designed to accelerate CT workflows, enhance diagnostic confidence, and maximize equipment up-time, helping imaging services to enhance patient outcomes, improve department efficiency, reduce operational costs, and meet ambitious financial objectives. CT 5100 – Incisive – with CT Smart Workflow [1] includes Philips' Tube for Life guarantee, which over the lifetime of the scanner can potentially lower operating expenses by an estimated USD 420,000 [2][3]. This newest CT innovation from Philips also provides access to Philips' Technology Maximizer program, which provides users with the latest software and hardware updates as they are released. "With the combination of CT 5100 – Incisive – and CT Smart Workflow, we have embedded AI into the tools that radiology departments use every day so they can apply their expertise to the patient, rather than unnecessary distractions associated with the CT imaging itself," said Frans Venker, General Manager of Computed Tomography at Philips.

AI has, by now, proven its power and impact. The artificial intelligence space is constantly evolving and improving with every passing day. Tech companies and researchers are investing big in bringing out innovations due to the massive potential the impact of AI can hold on the world's biggest problems. As we head towards the end of 2021, let us look back at some of the major AI innovations and incidents that took centre stage this year. OpenAI released DALL·E, a 12-billion parameter version of GPT-3 trained to generate images from text descriptions, using a dataset of text-image pairs.

This Web Application can recognize which numbers were drawn by you. To do this it uses Machine Learning (actually Deep Learning) techniques for predicting (determining) which digits were drawn by you on the canvas. It was trained (we refer to training as the way our model learn to predict correctly the given inputs) using two python frameworks for Machine Learning Tensorflow, Keras and another JavaScript framework used for inference (something like using a pre-trained model to make predictions) the TensorflowJS. For more information about the model used for inference, click on the Model Card.