Artificial Intelligence

Let's start by unpacking LLM-based approaches, also known as Large Language Models. These models, like LAMA 3, are at the forefront of natural language processing and understanding. LAMA 3, for instance, leverages the power of large-scale language models to tackle a wide range of tasks, from text generation to question answering, with unprecedented accuracy and efficiency. Its applications in bioinformatics are vast, including analyzing biomedical literature, extracting meaningful insights from clinical notes, and even aiding in drug discovery by predicting chemical properties and interactions. --- Send in a voice message: https://podcasters.spotify.com/pod/show/sadik-bhattarai/message

Embark on a journey to master the art of machine learning with our podcast, "Unlocking the Path." Whether you're an aspiring data scientist or a seasoned professional looking to enhance your skills, this podcast is your guide to success in the world of artificial intelligence. Join us each week as we explore the essential prerequisites and foundational knowledge needed to excel in a career in machine learning. From mastering Python programming and data analysis techniques to understanding the core concepts of machine learning algorithms, we cover it all. With insightful discussions, practical tips, and expert interviews, "Unlocking the Path" equips you with the tools and resources to take your skills to the next level. Whether you're just starting your journey or aiming to advance your career, our podcast provides invaluable insights and guidance every step of the way. Prepare yourself for the challenges and opportunities ahead as we dive deep into the exciting realm of machine learning. Subscribe to "Unlocking the Path" today and unlock the door to a fulfilling and rewarding career in artificial intelligence. --- Send in a voice message: https://podcasters.spotify.com/pod/show/sadik-bhattarai/message

AI has been making inroads in drug discovery for the past decade. According to a recent analysis, biotech companies using an AI-first approach have more than 150 small-molecule drugs in discovery and more than 15 already in clinical trials --- Send in a voice message: https://podcasters.spotify.com/pod/show/sadik-bhattarai/message

Machine learning and deep learning are becoming increasingly successful in addressing problems related to bioinformatics. This is due to their ability to parse and analyze large amounts of complex biological data, learn from the data, and use that learning to make intelligent decisions. One of the reasons why machine learning is important in bioinformatics is that it provides a way to analyze vast amounts of data generated by next-generation sequencing technologies, which have revolutionized the field of genomics. Machine learning algorithms can identify patterns in these large datasets and help researchers make sense of the complex relationships between genetic variants and disease phenotypes. Similarly, deep learning techniques, which are a subset of machine learning that utilize neural networks, have been successfully applied to problems such as protein structure prediction, drug discovery, and disease diagnosis. Deep learning can extract meaningful features from complex biological data and make accurate predictions based on those features. Overall, machine learning and deep learning are critical tools in bioinformatics research, allowing researchers to analyze large, complex datasets and make sense of the relationships between biological variables. These technologies are being used by leading bioinformatics companies and research institutions to drive breakthroughs in areas such as personalized medicine, drug discovery, and disease diagnosis. --- Send in a voice message: https://podcasters.spotify.com/pod/show/sadik-bhattarai/message

Machine learning is a type of artificial intelligence (AI) that enables software applications to learn from data and make predictions or decisions without being explicitly programmed to do so. It is a rapidly growing field that is impacting every industry, from healthcare to finance to transportation [1]. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output value within an acceptable range of accuracy. The algorithms can be trained to identify patterns in large datasets, and use those patterns to make predictions about new data. There are two primary types of machine learning: supervised and unsupervised. Supervised machine learning is the most common type used today, and it involves training a model on labeled data. In contrast, unsupervised machine learning involves training a model on unlabeled data and letting it find patterns on its own . The appeal of machine learning lies in its ability to help solve complex problems and make predictions that were previously impossible or difficult to achieve. In today's generation, machine learning is being used to address a wide range of issues, including healthcare, education, climate change, and more. For example, machine learning algorithms are being developed to predict the risk of disease, identify the best treatment options, and optimize medical resource allocation. Machine learning is also being used in education to personalize learning experiences for students and improve student outcomes. In summary, machine learning is a powerful tool that can be used to solve complex problems and make predictions that were previously impossible. It is being used in a wide range of industries to improve outcomes and drive innovation. With the increasing availability of data and advances in computing power, it is likely that machine learning will continue to play an important role in shaping our world. --- Send in a voice message: https://podcasters.spotify.com/pod/show/sadik-bhattarai/message

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"Brought to you by [Sadik Bhattarai]. The future is now." This script aligns with the recommended approach of starting with the ultimate aim and using a powerful call-to-action to drive the listener to a specific action. The script also includes direction notes for the tone and style of the narration, as seen in Example. Finally, for those struggling with what to include in a short radio spot, 30-second radio ad script examples can be a helpful resource --- Send in a voice message: https://podcasters.spotify.com/pod/show/sadik-bhattarai/message

Machine learning as a part of Artitificial Intelligence, it is gaining more popularity in different apllication and scope activities. --- Send in a voice message: https://podcasters.spotify.com/pod/show/sadik-bhattarai/message

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