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The article explores the pivotal role of artificial intelligence (AI) and machine learning (ML) in modern technology, revolutionizing industries and enhancing various aspects of daily life by enabling computers to learn from data, identify patterns, and make decisions autonomously. It also delves into the significance of open source languages like Python, R, and Julia in AI/ML development, highlighting their accessibility, rich libraries, and active communities, which foster collaboration.

Nobody at the time called Clippy an AI, but at heart what we're seeing in the AIs of today is a development of the same thing. The current crop of AIs are essentially algorithms, dependent on their training data for the responses they give to prompts. BUILD A GAMING POWERHOUSE The question of artificial intelligence has been a hard one to get away from, with ChatGPT hitting the headlines as both an amazing scientific advance and the harbinger of the end of civilization. [Extracted from the article]

The article focuses on the texts brought together to explore a wide range of vital and deadly experiences. Topics include considered some have been able to create a softness in which it is good to surrender, while others are sharp, sharp and examines they have in common is to be carried by an immodest writing, mimicking this capacity that blood also has to interfere in the faults and to coagulate the breaches.

Apple's latest iPhones, the iPhone 16, have a new feature called the Camera Control button. This button, located on the lower right side of the phone, allows users to quickly access the camera and take photos. It is designed to replicate the experience of using a DSLR camera's shutter button. The button also has other functions, such as toggling through camera options and adjusting zoom levels. The iPhone 16 Pro models have slightly larger screens and thinner borders, but the overall design is similar to previous models. The phones also come with more powerful processors and improved battery life. The prices for the new iPhones remain the same as previous models. [Extracted from the article]

Consensus, a startup utilizing AI technology, has raised over $11 million in funding to develop a search engine for scholarly work and health topics. The search engine currently has 400,000 monthly active users, including students, doctors, and health-conscious consumers, who rely on it to answer a wide range of questions. Consensus aims to differentiate itself from competitors by providing more accurate results and features tailored to researchers' needs. The funding round was led by Union Square Ventures, with participation from other investors. The startup currently has 12,000 paying users and is on track to generate $1.5 million in annual revenue. [Extracted from the article]

JPMorgan Chase has implemented a generative artificial intelligence (AI) product called OpenAI's ChatGPT to serve as a research analyst. The bank has provided its asset and wealth management division with access to a language model known as LLM Suite, which helps with writing, idea generation, and document summarization. This move follows a similar initiative by rival firm Morgan Stanley, which launched a chatbot powered by GenAI and OpenAI to provide financial advisors with quick access to the company's intellectual capital. Currently, 50,000 JPMorgan employees have access to the AI chatbot. [Extracted from the article]

The article focuses on the challenges and solutions in the realm of generative Artificial Intelligence (AI). Topics include the collaborative efforts of the open source community in advancing generative AI applications, the challenges and pitfalls associated with generative AI, and strategies for overcoming these challenges through techniques like model distillation, pruning, and quantisation and also discusses the scope of generative AI in India across various sectors.

A study conducted by researchers at Inonu University in Malatya, Turkey, has developed a new model called BioGraphSum for text summarization in the field of biomedicine. The model aims to reduce dependence on the Unified Medical Language System (UMLS) by graphically conceptualizing sentences as nodes and identifying influential nodes for summarization. The model was tested against a corpus of 450 scientific research articles and showed significant improvements in precision-based and f-score-based metrics compared to existing models. The study provides new insights into the power of graphs in medicine for effective text summarization. [Extracted from the article]

Discover Financial Services partnered with Google Cloud to integrate Vertex generative AI into its customer care centers. With these tools, its contact center agents will have access to intelligent document summarization and real-time search assistance, according to a press release.... [ABSTRACT FROM AUTHOR]

A recent study conducted by the Department of Radiology in Jaen, Spain, explored the use of natural language processing and machine learning to automatically generate conclusions for neuroradiology MRI reports. The researchers applied a fine-tuned Text-To-Text Transfer Transformer (T5) model to a dataset of 232,425 Spanish MRI reports. The results showed that the T5 models achieved high scores in various evaluation metrics and were found to be as good as or even better than manually generated conclusions by radiological experts in 75% of cases. This research highlights the potential and effectiveness of customizing pre-trained models for neuroradiology, emphasizing the importance of dedicated language models for radiology report summarization. [Extracted from the article]

A preprint abstract from medrxiv.org discusses the evaluation of large language models (LLMs) for generating emergency department (ED) discharge summaries. The study investigates the performance of GPT-4 and GPT-3.5-turbo in summarizing ED clinician notes and evaluates the prevalence and type of errors in the generated summaries. The results show that while LLMs can generate accurate summaries, they are prone to hallucinations and omissions of clinically relevant information. The study emphasizes the importance of understanding and addressing these errors to ensure patient safety. [Extracted from the article]

A systematic review of large language models (LLMs) in patient care was conducted to examine their current applications and limitations. The review included 89 studies across 29 medical specialties, primarily focusing on models based on the GPT-3.5 and GPT-4 architectures. The analysis identified design limitations, such as lack of medical domain optimization and data transparency, as well as output limitations, including non-reproducibility, incorrectness, and bias. This study provides a foundational framework and taxonomy for the implementation and evaluation of LLMs in healthcare settings. However, it should be noted that this preprint has not yet undergone peer review. [Extracted from the article]

Samsung Electronics will be featuring Baidu Inc.'s Ernie Bot in its new Galaxy S24 smartphone series in China. The partnership aims to enhance the AI capabilities of the smartphones, including text summarization, organization, and translation. Baidu's Ernie AI is seen as a major player in the Chinese AI market and this collaboration with Samsung could help boost its presence. Samsung's market share in China has declined in recent years, and showcasing Ernie AI could attract existing users and help the company establish itself in the foldable smartphone category. [Extracted from the article]

Samsung Electronics Co. has announced that it will integrate Baidu Inc.'s Ernie Bot into its new Galaxy S24 smartphone series in China. The partnership aims to enhance the AI capabilities of the smartphones, including text summarization, organization, translation, and the "circle to search" feature. This move is part of Samsung's efforts to expand its presence in the Chinese market, and the integration with Baidu's AI tools may help attract more consumers to switch from Apple's iPhone or local brands. [Extracted from the article]

Microsoft is upgrading its AI engine, Copilot, to GPT-4 Turbo, the latest version of OpenAI's ChatGPT engine. This new version has been trained on data up to April 2023 and has a quadrupled query size, allowing users to input larger amounts of text for summarization. Copilot now includes a code interpreter feature for programmers, the ability to summarize YouTube videos, and the capability to rewrite text without changing the content. Microsoft has invested $10 billion in OpenAI and holds a 49 percent stake, with recent tensions over control of the organization. [Extracted from the article]

Microsoft 365 Copilot, formerly known as Microsoft 365 Copilot, is an AI assistant integrated into Microsoft workplace apps like Word, Outlook, Teams, and Excel. It uses genAI features to improve productivity and accessibility through natural language interactions. The system includes Microsoft 365 apps, Microsoft Graph, and OpenAI models. While there are potential risks in using the tool, Microsoft aims to provide a more functional assistant for work. Copilot is available for enterprise and smaller business customers at an additional cost. It can attend meetings, generate summaries and action items, turn Word documents into PowerPoint slides, and search for information. Microsoft plans to integrate Copilot with third-party apps and expand its capabilities. Early customers have found value in using Copilot for tasks like summarizing information and preparing for meetings. However, there are risks associated with generative AI tools, such as incorrect information and data protection concerns. Despite these risks, Copilot offers productivity benefits and privacy and security controls. [Extracted from the article]

Researchers from Hong Kong University of Science and Technology have conducted a survey on hallucinations in natural language generation (NLG). NLG has seen significant advancements in recent years, particularly in areas such as abstractive summarization and dialogue generation. However, deep learning-based NLG systems are prone to generating unintended text, leading to hallucinations. The survey provides an overview of research progress and challenges in addressing this issue, with a focus on metrics, mitigation methods, and task-specific research progress. The goal of the survey is to facilitate collaborative efforts among researchers in tackling the challenge of hallucinated texts in NLG. [Extracted from the article]

A recent report from the U.S. Food and Drug Administration (FDA) discusses the development of automated methods for generating food effect summaries. These summaries are important for providing guidance to the pharmaceutical industry on fasting and fed bioequivalence studies. The report introduces an approach called iterative prompting, which uses large language models like GPT-4 to improve the accuracy and efficiency of automated text summarization. The study found that GPT-4 performed better than ChatGPT in generating summaries that were factually consistent with the reference summaries. The researchers believe that GPT-4 has the potential to improve the efficiency of the guidance development process and promote the development of generic drug products. [Extracted from the article]

This article highlights Canada's prominent role in the field of artificial intelligence (AI). Canadian computer scientists, such as Yoshua Bengio and Geoffrey Hinton, persisted with neural networks despite initial skepticism, leading to breakthroughs in deep learning. Unlike previous generations of Canadian AI companies that were often acquired or relocated to Silicon Valley, the current generation of startups and scale-ups are determined to stay in Canada and develop AI's next big application. Cohere, a Toronto-based startup founded by former Google Brain employees, is gaining attention for its large language models (LLMs) that improve text generation, document summarization, and search. The Canadian AI scene is thriving, with over 1,100 privately held generative AI companies raising $45 billion since the start of 2020. [Extracted from the article]

For more information on this research see: Evaluation of text summarization techniques in healthcare domain: Pharmaceutical drug feedback. Keywords: Drugs and Therapies; Technology EN Drugs and Therapies Technology 1335 1335 1 10/03/23 20231003 NES 231003 2023 OCT 2 (NewsRx) -- By a News Reporter-Staff News Editor at Clinical Trials Week -- A new study on technology is now available. [Extracted from the article]

* Natural Language Processing Specialization from Coursera.This intermediate-level set of four courses is intended toprepare students to design NLP applications such assentiment analysis, translation, text summarization, andchatbots. NLP applications Machine translation is a powerful NLP application, butsearch is the most used. Natural language processing definition Natural language processing (NLP) is the branch ofartificial intelligence (AI) that deals with trainingcomputers to understand, process, and generate language. [Extracted from the article]

Keywords for this news article include: University of Texas Health Science Center Houston, Medical Informatics, Health Information Technology. Keywords: Health Information Technology; Medical Informatics EN Health Information Technology Medical Informatics 3993 3993 1 05/29/23 20230602 NES 230602 2023 JUN 2 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Investigators discuss new findings in medical informatics. [Extracted from the article]

In response, we develop a pre-trained language model in the chest radiology domain, named ChestXRayBERT, to solve the problem of automatically summarizing chest radiology reports. (Institute of Electrical and Electronics Engineers - www.ieee.org/; IEEE Transactions on Multimedia - ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6046) Our news correspondents report that additional information may be obtained by contacting Libin Yang, Northwestern Polytechnic University, School of Automation, Xian 710072, People's Republic of China. Keywords: Xi'an; People's Republic of China; Asia; Blood Research; Health and Medicine; Radiology EN Xi'an People's Republic of China Asia Blood Research Health and Medicine Radiology 337 337 1 05/15/23 20230518 NES 230518 2023 MAY 18 (NewsRx) -- By a News Reporter-Staff News Editor at Blood Weekly -- Investigators publish new report on Blood Research. [Extracted from the article]

Sedgwick, a global insurance claims administrator, has implemented generative artificial intelligence (genAI) to streamline its document summarization process. The genAI tool, called Sidekick, uses OpenAI's GPT-4 to accurately summarize multi-page claims documents. Sedgwick has successfully piloted the tool, processing over 14,000 documents and receiving overwhelmingly positive feedback. The company plans to expand the use of genAI and integrate it into their claims system to further improve efficiency and provide prescriptive recommendations to examiners. [Extracted from the article]

We describe a task-based evaluation to determine whether multi-document summaries measurably improve user performance when using online news browsing systems for directed research. We evaluated the multi-document summaries generated by Newsblaster, a robust news browsing system that clusters online news articles and summarizes multiple articles on each event. Four groups of subjects were asked to perform the same time-restricted fact-gathering tasks, reading news under different conditions: no summaries at all, single sentence summaries drawn from one of the articles, Newsblaster multi-document summaries, and human summaries. Our results show that, in comparison to source documents only, the quality of reports assembled using Newsblaster summaries was significantly better and user satisfaction was higher with both Newsblaster and human summaries. [ABSTRACT FROM AUTHOR]

In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that these focused named entities are useful for many natural language processing applications, such as document summarization, search result ranking, and entity detection and tracking. We propose a statistical model for focused named entity recognition by converting it into a classification problem. We then study the impact of various linguistic features and compare a number of classification algorithms. From experiments on an annotated Chinese news corpus, we demonstrate that the proposed method can achieve near human-level accuracy. [ABSTRACT FROM AUTHOR]