Upcoming AI based Technologies in Research
1. DEEPFAKE IS THE FUTURE OF CONTENT CREATION
What is Deepfake?
AI-generated fake videos are becoming more common. Before going in detail, Lets know about what is deepfake.
The 21st century’s answer to Photoshopping, deepfakes use a form of artificial intelligence called deep learning to make images of fake events, hence the name deepfake. Want to put new words in a politician’s mouth, star in your favourite movie, or dance like a pro? Then it’s time to make a deepfake. Deepfakes are synthetic media in which a person in an existing image or video is replaced with someone else’s likeness.
How DeepFakes are made?
One way to make deepfakes uses what’s called a generative adversarial network, or Gan. A Gan pits two artificial intelligence algorithms against each other. The first algorithm, known as the generator, is fed random noise and turns it into an image. This synthetic image is then added to a stream of real images – of celebrities, say – that are fed into the second algorithm, known as the discriminator. At first, the synthetic images will look nothing like faces. But repeat the process countless times, with feedback on performance, and the discriminator and generator both improve. Given enough cycles and feedback, the generator will start producing utterly realistic faces of completely non-existent celebrities.
Uses of DeepFake
1.This deep fake can be used for Investment purpose and Commercial use i.e., it can be used for training courses with different languages.
2. Aids in Future conversation with Grandchildren.
2. How AI is Revolutionizing Drug Discovery
AI is revolutionizing the healthcare and pharmaceutical industries, offering unprecedented efficiency in drug discovery processes. This technology significantly accelerates the identification of viable drug candidates by analyzing large datasets that include genomic, biological, and clinical information. In 2024, the pharmaceutical industry increasingly relies on AI to reduce costs, streamline processes, and bring life-saving drugs to market faster.
AI in Drug Target Identification
AI plays a crucial role in identifying biological targets for drug development. By leveraging machine learning and deep learning algorithms, AI systems analyze vast datasets, including patient records, genetic sequences, and disease pathways. This analysis helps pinpoint biomarkers that reveal disease mechanisms and target specific molecules in drug creation. For instance, AI models have been used to predict which proteins can be altered to halt disease progression, enabling researchers to concentrate on the most promising drug candidates.
AI for Drug Repurposing
AI excels in drug repurposing by evaluating existing drugs for new uses. It analyzes biochemical interactions and patient data to identify new applications for these drugs, which have already been safety-tested. This approach saves time and resources and holds promise for discovering treatments for rare or hard-to-treat conditions.
Example
Companies like Insilico Medicine is an AI-driven biotechnology company that uses artificial intelligence to discover new drug candidates. They have developed an AI platform called Pharma.AI, which has successfully identified potential drugs for various diseases, including fibrosis. One of their AI-generated anti-fibrotic drugs has progressed to Phase 2 clinical trials as of 2024. Insilico’s use of AI in drug discovery demonstrates the practical application of AI in speeding up the identification and testing of new treatments.
AI in Clinical Trials & Personalized Medicine
AI enhances clinical trials and personalized medicine by improving efficiency and precision. In clinical trials, AI predicts optimal patient groups, forecasts drug efficacy, and monitors safety, using simulations to anticipate adverse reactions and speed up safety assessments. In personalized medicine, AI analyzes genomic data to tailor treatments to individual profiles and continuously adjusts therapies based on real-time data, boosting treatment effectiveness.
3. How AI is Transforming Space Exploration
AI is revolutionizing space exploration by enhancing mission efficiency, autonomy, and data analysis capabilities. As of 2024, AI is becoming integral to space agencies and research organizations, driving forward advancements and deepening our understanding of the cosmos.
AI in Autonomous Spacecraft Navigation
AI significantly improves autonomous spacecraft navigation by enabling real-time, adaptive decision-making. Utilizing sophisticated neural networks and control algorithms, AI systems allow spacecraft to autonomously navigate and avoid obstacles. This technology enhances mission efficiency and reduces reliance on ground control, ensuring more precise and independent operations.
AI in Astronomical Data Analysis
AI transforms astronomical data analysis through advanced deep learning models and data-mining techniques. AI systems process vast amounts of data from space observatories, uncovering patterns and identifying celestial phenomena with unprecedented accuracy. This technology accelerates scientific discoveries and enhances our understanding of the universe.
AI in Mission Planning and Management
AI revolutionizes mission planning and management by employing simulation-based optimization and predictive analytics. AI-driven tools create and evaluate multiple mission scenarios, optimizing resource allocation and risk management. This leads to more effective mission strategies and improved operational outcomes.
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