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Artificial intelligence (AI) has revolutionized healthcare by changing how we identify, treat, and keep track of patients. By enabling more individualized treatments and generating more accurate diagnoses, this technology is significantly enhancing healthcare research and results. Medical practitioners can find disease signs and patterns that would otherwise go unnoticed because to AI’s rapid analysis of enormous volumes of clinical data. AI has a wide range of possible uses in healthcare, from predicting results from electronic medical records to analyzing radiological images for early detection. Healthcare systems may become smarter, faster, and more efficient in treating millions of people globally by utilizing artificial intelligence in clinics and hospitals. It started with IBM’s Watson artificial intelligence system, which was designed to provide precise and speedy answers to queries. The introduction of a healthcare-specific version of Watson by IBM in 2011 that concentrated on natural language processing—the technology used to comprehend and interpret human communication—is mentioned in articles about artificial intelligence in healthcare. These days, in addition to IBM, other digital behemoths like Apple, Microsoft, and Amazon are making more and more investments in AI technology for the medical field. Artificial intelligence has incredibly exciting potential applications in healthcare. AI in healthcare is predicted to significantly alter how we handle medical data, identify illnesses, provide cures, and possibly stop them in their tracks. Medical personnel can save time, cut expenses, and enhance medical records administration by employing artificial intelligence in healthcare to make better judgments based on more accurate information. AI in healthcare has the potential to revolutionize everything from finding novel cancer treatments to enhancing patient experiences, paving the path for a time when patients will receive high-quality care and treatment more quickly and precisely than in the past. Machine Learning By improving medical diagnosis and treatment, machine learning—a crucial aspect of AI applied in healthcare—has drastically changed the industry. Algorithms can find patterns and make previously unheard-of accurate predictions about medical outcomes by analyzing enormous volumes of clinical data. Healthcare practitioners can enhance treatments and cut costs by using this technology to analyze patient information, medical imaging, and find new therapies. Precise illness diagnosis, tailored therapies, and the identification of minute variations in vital signs that may point to possible health problems are all made possible by machine learning. The most popular use, precision medicine, uses supervised learning to forecast successful treatment plans based on patient-specific data. Furthermore, deep learning—a branch of artificial intelligence—is employed in the medical field for tasks like natural language processing-based speech recognition. Natural Language Processing A type of artificial intelligence called natural language processing (NLP) makes it possible for computers to understand and utilize human language. The healthcare sector is changing as a result of this type of AI. Numerous health data applications, including enhancing patient care through increased diagnosis accuracy, expediting clinical procedures, and offering more individualized services, make use of natural language processing (NLP). For instance, by extracting valuable information from health data, NLP can be used to effectively diagnose ailments in medical records. It can also be used to determine which medications and therapies are appropriate for each patient, or even to forecast possible health hazards by using historical health data. Additionally, NLP gives medical professionals strong capabilities for handling vast volumes of intricate data. Natural language processing is turning out to be a very useful technology in the medical field. It enables doctors to employ artificial intelligence to detect diseases more precisely and treat patients more individually. This type of artificial intelligence in healthcare is rapidly becoming essential to the contemporary healthcare sector and is probably going to advance further and find usage in new areas. Rule-based Expert Systems The most common AI technology in healthcare during the 1980s and following years was expert systems built on versions of “if-then” principles. Even now, clinical decision support is one of the most common applications of artificial intelligence in healthcare. With their software packages, many electronic health record systems (EHRs) now provide a set of guidelines. In order to create a comprehensive set of rules in a particular field of knowledge, expert systems typically require human specialists and engineers. They are simple to follow and process, and they work effectively up to a point. But once the number of rules becomes too much—typically beyond a few thousand—they may start to clash and disintegrate. Additionally, if there is a substantial shift in the field of knowledge, Diagnosis and Treatment Applications For the past 50 years, the main application of artificial intelligence (AI) in healthcare has been in the diagnosis and treatment of illness. Despite its potential for precise illness diagnosis and treatment, early rule-based systems not entirely embraced for use in clinical settings. Their diagnostic abilities were not appreciably superior to those of humans, and their integration with medical record systems and clinical workflows was subpar. However, integrating artificial intelligence (AI) into healthcare for diagnostic and treatment plans—whether algorithmic or rules-based—with clinical processes and electronic health record (EHR) systems can frequently be challenging. When compared to the accuracy of recommendations, integration problems inside healthcare institutions have been a bigger obstacle to the broad use of AI in healthcare.A large portion of medical software companies’ AI and healthcare capabilities for diagnosis, therapy, and clinical trials are stand-alone and only cover a single area of care. Although they are still in the early stages, some EHR software providers are starting to incorporate basic AI-powered healthcare analytics features into their product lines. Providers will need to either carry out significant integration projects themselves or take advantage of third-party vendors who have AI capabilities and can integrate with their EHR in order to fully benefit from the use of AI in healthcare with a stand-alone EHR system.

In every industry, applying strategically developed competition insights is absolutely necessary. Now, more than ever, it’s become straightforward with the help of new business tools driven by AI due to their unmatched power, speed, and precise data options. These tools are invaluable for any business, be it a nascent startup or a leading enterprise, striving for optimal strategic planning and sustainable growth. In this article let’s review some top AI tools enabling automation and transforming the landscape of advanced competitive market research. 1. Crayon Competing in the sphere of real time competitive intelligence Crayon is a big player. Crayon’s forte is information gathering where they follow digital activities of a particular competitor such as how they change prices, launch new products and what marketing strategy they employ. Data analysis is crucial for every business and that is what Crayon helps with to its customers. This level of precision allows teams to outrun competitors in a timely manner, and most importantly, react immediately to changes. With Crayon, sales teams beat objections and claim rebuttals with rock-solid, fresh evidence, and marketing adjusts the text of ads to what is trending in the industry. Crayon has also incorporated tools helping in improving collaboration among different departments so that intelligence can be shared, accessed and made use of. For those looking for a thorough single source platform, Crayon is exactly what serious market researchers need. 2. Kompyte When it comes to competitive research, Kompyte goes above and beyond in automation. This AI-powered tool keeps tabs on your competitor’s digital activities such as social media posts, advertisement updates, and website changes, sending alerts as updates happen in real-time. What sets Kompyte apart, however, is the smart recommendation engine which tells you the next steps to take with the data. From completing page updates to modifying email copy, the tool makes tailored suggestions based on market movements. In addition, Kompyte assists in the construction of battle cards as well as sales enablement ensuring that sales reps are always one step ahead in conversations. For teams that want to streamline most of the manual monitoring to the bare minimum, action-oriented tracking, automation, and focus on results, Kompyte helps. 3. Similarweb When it comes to analyzing the traffic a website gets and the competitors it has, Similarweb is unrivaled. For any website, including the competitors, it provides information on the traffic sources, engagement metrics, audience interests, and referral paths. This AI-driven tool offers an all-inclusive picture of an industry’s landscape regarding competition’s content traction, keyword positioning, and overall content strategy effectiveness. Similarweb empowers informed decision-making for new SEO campaigns or digital product launches. Its benchmarking capabilities are exceptional, helping with understanding brand positioning within the industry competitively. 4. SpyFu For competitive keyword research and PPC strategy, SpyFu is the king. It lets you “spy” on your competitors’ Google Ads campaigns, keyword rankings, and even how well they performed historically. Perhaps the most useful feature is the downloader tool that lets you download your competitors’ most profitable keywords and ad copies. This allows you to fill gaps in your strategy or copy what’s working for others. Alongside those features, SpyFu gives AI-powered recommendations for improving your SEO and ad spend suggesting expenditure optimization. It is perfectly suited to marketers and SEO professionals who want to gain an upper hand without strategies. SpyFu’s clear UI paired with well-organized and thorough reports ensure that the user experience remains smart and simple. 5. Brandwatch Social media conversations, Brandwatch’s forte, are cannibalized for insights using AI. Forums, news outlets, and other social media platforms are not exempt. With Domain Sentiment Analysis (DSA) a form of natural linguistics processing, Brandwatch categorizes emotions, conversations, and activities. This helps track impression management, find advertisers, and identify trends within an industry ahead of time. Data Studio and Google slack provides real time report integration. People do not have to censor themselves, hence Blackwatch’s slack provides access to what consumers think about competitor brands.6. Crystalknows Crystalknows combines competitive research with behavioral analysis. Through information publicly available, this AI tool forecasts persona and communication types of your business competitors and prospective clients. Imagine knowing the thought processes, decision-making methods, and negotiation strategies of rival CEOs. With Crystal, you don’t have to imagine it. It uses behavioral AI to create personality profiles useful for sales, client relations, and even internal collaborations. While it may sound like something out of science fiction, Crystalknows tailors messages to personas they wish to address, making it highly effective. For those seeking advanced data analytics with human insights, Crystal is a perfect tool. 7. Owler Owler takes competitive tracking into the world of crowdsourcing. Through the application of artificial intelligence, it provides alerts and insights as well as growth trend data through real user contributions from business specialists. The Owler Daily Snapshot emails inform you of your competitors’ funding and press activities, as well as leadership changes and mentions in the news. Each day feels like a tailored newspaper is sent directly to you. The platform additionally offers CEO approval ratings, estimated revenue figures, and social sentiment scores. It is easier than ever to keep tabs on even the most niche players in your market with over 15 million company profiles on Owler. If you are after a no cost or low cost option to stay informed, this platform is fabulously efficient. 8. Quantcast The main focus of Quantcast is AI audience insights; it is all about that. It gathers audience and market information in real time and provides you with a reliable picture of what is happening. Quantcast uses Ara™, its proprietary AI engine, to analyze billions of data points and identify patterns of user activity, interests, and demographics. It shows the websites your competitors’ audience visit and strategize how you can capture them. It aids particularly in advertisement targeting and personalization because marketers need to make more relevant advertisements. Quantcast also provides predictive analytics capabilities, allowing you to anticipate changes in the market and audience needs ahead of time. 9. BuzzSumo  If

Nowadays, artificial intelligence (AI) is not a sci-fi idea. It has the potential to become a fundamental component of public sector operations by 2025, revolutionizing the way agencies make choices and interact with their constituents. Government organizations can increase productivity, make better decisions, and offer citizens better services by taking the lead in AI-powered innovation. 50% of agencies reported high levels of AI maturity, which correlates to mature behaviors like embracing an innovation culture and piloting generative AI use cases to drive mission impact, according to a recent Google-commissioned IDC study that polled 161 federal Chief AI Officers and other AI decision makers. Let’s examine five AI trends that we think will influence the public sector in the upcoming year. Trend #1: Multimodal AI: Unleashing the power of context Imagine a future in which artificial intelligence (AI) is able to comprehend and evaluate data from a variety of sources, including text, photos, videos, and even speech. This is multimodal AI’s power. The adoption of AI will be crucial this year, mostly due to multimodal learning and the contextual awareness it makes possible. In order to enhance decision-making, anticipate climate-related dangers, and upgrade public infrastructure, multimodal AI will eventually allow agencies to evaluate data at the municipal and state levels and integrate it with data from other sources, such as Google Earth Engine, Google Maps, Waze, and public data sets. The Hawaii Department of Transportation (HDOT) is better equipped to tackle climate issues thanks to Google AI. They may prioritize investments and evaluate risk by utilizing Google Earth Engine and Google Cloud to implement a Climate Resilience Platform. Trend #2: AI agents: The evolution from chatbots to multi-agent systems Simple chatbots of the past have given way to advanced AI agents of the future that can manage the trickiest jobs. These agents have the ability to plan, reason, and even pick up knowledge from their interactions. Government workers will be able to work and code more effectively in the future, manage their apps, obtain deeper insights from data, recognize and address security issues, and realize their finest ideas with the aid of AI agents. Google AI-powered virtual agents are being used in Sullivan County, New York, to serve more residents more quickly, day or night. Sullivan County came up with a system that helps citizens outside of regular business hours while allowing government employees to concentrate on important tasks despite having a small workforce and budget. Trend #3: Assistive search: The next frontier for knowledge work Artificial Intelligence is already changing how we obtain and comprehend information. Governments can increase the precision and effectiveness of scanning large datasets with generative AI. Agencies can increase the value and accessibility of their data by investing in automated metadata tools, semantic search, and sophisticated document transcription. From materials science and bioinformatics to human performance enhancement, the Air Force Research Laboratory (AFRL) is utilizing Google Cloud’s state-of-the-art artificial intelligence (AI) and machine learning (ML) capabilities to address challenging problems in a variety of fields. To further its objective of creating and transferring cutting-edge technology to the air, space, and cyberspace forces, AFRL is utilizing AI and cloud computing. Trend #4: AI-powered constituent experience: seamless and personalized AI will contribute to bettering citizen experiences by 2025. By allowing citizens to swiftly and simply explore government websites and services—like applying for permits and licenses—offered in many languages and available around-the-clock, AI-powered tools and technology can promote tighter citizen-government connections and increase confidence. The Wisconsin Department of Workforce Development (DWD) was able to expedite overall response times and scale the state’s response to unemployment insurance claims by collaborating with Google AI. In order to administer the UI program to Wisconsinites in need of financial aid in an honest manner, they were also effective in weeding out bogus claims. Trend #5: Security gets tighter— and tougher— with AI The dangers posed by AI are growing in frequency. But AI can also be a very effective tool for improving security. AI can assist in safeguarding sensitive data and government systems by automating threat detection, evaluating enormous volumes of data, and swiftly responding to problems. Agencies must give security first priority as AI pervades government and citizen services more and more in order to counter risks like disinformation and deepfakes. Every week, 90 billion cyberattacks target New York City. We must reduce those 90 billion occurrences to no more than 50 or 60 items. Without a great deal of artificial intelligence and automated decision-making capabilities, we couldn’t accomplish that.” New York City’s Chief Technology Officer, Matthew Fraser. The opportunity ahead AI is already generating a lot of excitement among public sector organizations around the nation, which are utilizing it to boost productivity, improve decision-making, and better serve their clients. In the future, we anticipate that agencies will select and fund AI leaders who strengthen AI governance, foster public confidence, and make investments in a workforce strategy that prioritizes AI and security. For AI to be developed and implemented responsibly and securely at all governmental levels, this will be essential.

With millions of users turning their images into animated visuals evoking the works of renowned Japanese animator Hayao Miyazaki, the Ghibli-style AI art fad has swept social media by storm. Well-known people like Elon Musk, Amitabh Bachchan, and Prime Minister Narendra Modi have joined the trend, increasing its appeal. But the viral trend has also spurred discussions regarding ethical AI-generated art use and copyright violation, especially with regard to systems trained on copyrighted creative works. Although opinions on the trend are still divided, one question still stands: who initiated it all? The Man Behind the Trend Grant Slatton, a software developer from Seattle, is recognized for having popularized the Ghibli-inspired AI art movement. Slatton shared an AI-generated image of his family and dog at the beach on X (previously Twitter) on Tuesday, just after OpenAI unveiled its updated image-generation tools. “Amazing alpha right now in sending your wife photos of y’all converted to Studio Ghibli anime,” he captioned the shot. Although AI-generated anime-style graphics have been around for a while, Slatton’s piece appears to have been the catalyst for the recent surge in interest. His tweet quickly became popular, receiving around 49 million views and more than 45,000 likes. Social media users started posting their own “Ghiblified” images, and the practice quickly grew into a worldwide sensation. A Wave of Positive Responses Slatton told Business Insider that he has received a ton of messages from people who share their photos that have been altered. He declared, “It’s the most net-positive day I’ve ever seen on Twitter.” He added that the most recent developments in OpenAI have greatly simplified the procedure. With straightforward commands like “convert to Studio Ghibli please,” the new model produces excellent anime-style visuals, in contrast to earlier iterations that needed specific cues. Even some detractors of AI-generated art have joined the bandwagon, despite worries about how AI may affect human creativity. Several requests were “heartwarming,” Slatton said, adding that he had manually processed more than 100 photos for customers who couldn’t utilize the service. The Ongoing Debate Discussions on AI-generated art are still contentious, despite the trend’s continued popularity on social media. Concerns about the ethical implications of AI tools trained on preexisting works have been raised by fans of Studio Ghibli and Miyazaki regarding the usage of AI to replicate their unique artistic styles. As the argument continues, millions of people are embracing the newest digital phenomenon, and the Ghibli-style AI art craze is showing no signs of slowing down. The AI-generated anime-style trend is here to stay, regardless of whether it is seen as a revolutionary development or a divisive topic. What Is The Studio Ghibli AI Trend? Users soon discovered that OpenAI could produce high-quality photographs with comparatively unconstrained copyright filtering after the company unveiled a new image generator. Although they are less common, wonky fingers and strange backdrop elements still exist, making it more difficult to tell AI photographs apart from the actual thing. Users tried a variety of cartoon series, including The Simpsons, Rick and Morty, and South Park, but Studio Ghibli was the most well-liked and trended on X (Twitter). Even while Studio Ghibli is known for its dark and tumultuous films, the animation studio is also well-known for its serene, reflective sequences in which painstakingly crafted figures merely gaze at the hand-drawn landscape. As a result, the studio’s name is frequently linked to warm, positive emotions. The Trend Goes Against The Ethos Of Studio Ghibli Fans of Studio Ghibli were surprised by the trend because it goes against the company’s and co-founder Hayao Miyazaki’s values to employ AI picture generators to mimic an artist’s distinctive style. The trend, according to many analysts, was in bad taste and devalued the meticulously developed aesthetics of an animation company that is renowned for its commitment to the craft. Oscar winner Miyazaki has made his opinions about generative AI quite apparent. He is the director of several of Ghibli’s most famous films, including Spirited Away, Princess Mononoke, My Neighbor Totoro, and The Boy and the Heron. Miyazaki was shown an AI-generated animation years before generative AI took over the internet. He denounced it, stating, “I strongly feel that this is an insult to life itself.” Miyazaki stops talking when the programmers explain that their goal is to build a machine that can draw like a human. Later, as he works, the director is seen reflecting on the new technology, stating, “I feel like we are nearing the end times.” Humans are becoming less confident in themselves. The irony of employing generative AI, a horribly energy-intensive technology, to mimic the studio’s style was pointed out by numerous reviewers. Many Studio Ghibli films emphasize the value of living in peace with nature and portray the grandeur of nature. The Ghibli trend’s novelty will probably fade shortly because it’s just another filter. However, the Ghibli picture flood demonstrates how generative AI is making art more and more disposable. A privacy nightmare in disguise, experts warn Although the viral trend of employing AI technologies to turn personal images into Studio Ghibli-style art has captured the attention of netizens, experts caution that the trend hides a darker reality where careless sharing might result in unexpected privacy breaches and data exploitation. Although these programs can seem innocuous, cybersecurity experts warn that their terms of service are sometimes ambiguous, creating concerns about what happens to user photos once they are processed. When OpenAI introduced the GPT-4o model, which enables users to make their own images in the aesthetic manner of the Japanese animation studio Studio Ghibli, the movement got underway. A small percentage of the numerous platforms claim that they either do not save the images or remove them after a single use. There is more than just face information in photos. They frequently contain secret metadata that might subtly reveal personal information, such as timestamps, location coordinates, and device specifications. According to Vishal Salvi, CEO of Quick Heal Technologies, these AI technologies make use of neural style transfer (NST)