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🤖 Building Effective AI Models: The Importance of 𝐑𝐞𝐩𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐯𝐞 Training Data 🌟The goal of #AI model training is to develop a model that can 𝐠𝐞𝐧𝐞𝐫𝐚𝐥𝐢𝐳𝐞, or make accurate predictions when given 𝐧𝐞𝐰 𝐝𝐚𝐭𝐚. 💡That's why 𝐫𝐞𝐩𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐯𝐞 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 is key in building any AI model —if it fails to capture the diversity and complexity of 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬, the resulting model will underperform during actual production scenarios and will be dismissed. #selfreminder #datascience #data #dataanalytics 

🤖 What Exactly is Machine Learning? Let’s Break It Down: Machine Learning (ML) is a type of Artificial Intelligence (AI) that enables machines to learn from data and improve over time without being explicitly programmed. How It Works: Data Input: Machines are fed large sets of data (e.g., resumes, customer interactions, or images). Pattern Recognition: The system identifies patterns or trends within the data. Learning: Based on these patterns, the machine makes decisions or predictions. Continuous Improvement: As it processes more data, the system refines its predictions and becomes smarter. Why It’s Important: ML is behind many of today’s technologies, from personalized recommendations to virtual assistants and automated processes. It helps businesses become more efficient, make data-driven decisions, and stay competitive in a tech-driven world. At CogniSoft, we’re embracing Machine Learning to offer AI-powered solutions to our clients. This is part of our broader transition into AI projects and digital marketing services, helping businesses grow and innovate. Stay tuned for more updates as we explore the exciting possibilities of AI! #MachineLearning #AI #TechInnovation #AIProjects #DataScience #DigitalMarketing #BusinessGrowth

Valuable information for CFOs interested in #AI and #machinelearning. The following text was generated using a #ChatGPT plugin for YouTube. It's pretty fascinating how quickly AI technology can be adopted and useful. We hope you enjoy it! **Early Innovations and Practical Applications** AI has improved significantly over decades, enhancing business processes like Optical Character Recognition (OCR) and automating data entry with near-perfect accuracy. It helps businesses digitize data and automate routine tasks, resulting in substantial efficiency gains. **Big Data and AI Implementation** For larger enterprises, AI systems provide deep insights by analyzing extensive data sets. These systems help in optimizing operations such as dynamic pricing and customer behavior analysis, offering significant returns on investment. **Machine Learning vs. Artificial Intelligence** There's often confusion between AI and machine learning. Machine learning involves systems that learn and adapt from data, refining their performance over time. Examples include spam filters and systems that analyze financial data to identify anomalies. **AI in Consumer and Business Applications** Major tech companies have driven AI advancements, with products like Siri, Alexa, and Google Assistant. These AI systems require significant computing power but offer major benefits, such as improved voice recognition and personalized user experiences. **Ethical and Regulatory Considerations** The rapid advancement of AI poses ethical and regulatory challenges. Issues such as privacy, and accountability in healthcare, law enforcement, and legal practice need careful consideration. The development and deployment of AI require balanced regulation to manage potential risks effectively. https://lnkd.in/ezj-kmpM

Generative AI content is prolific, but when it trains AI models, the outcome might not be as fluent as we'd hope. What happens when these models are fed their own output as training data? https://bit.ly/3XvDDVY

'Please die': Google's AI chatbot shocks student seeking help with homework - Business Standard: 'Please die': Google's AI chatbot shocks student seeking help with homework  Business Standard http://dlvr.it/TGDK9t #ai #artificialintelligence

For those just starting in the world of AI, here's a great course to understand the functional concepts. It's aimed at non-technical people who can democratize the concept. https://lnkd.in/eNiwGyZc #AI #IT

Not all AI is created equal. While Traditional AI follows strict rules to solve specific tasks, Generative AI takes it a step further—creating new, original content like text, images, and even code. In this carousel, we break down: - What each type of AI is - How they work - Key applications and strengths - Where they shine and their limitations Swipe through to learn how Generative AI is pushing the boundaries of creativity while Traditional AI powers structured, rule-based tasks. Which type of AI do you think is more impactful? Let’s discuss in the comments! OpenAI Google Premium AIMicrosoft IBM NVIDIA Salesforce Adobe #GenerativeAI #ArtificialIntelligence #AI #MachineLearning #Innovation #TechTrends Learning Resource:W3Schools.com

Explore AI prompts to create, edit, and get more done with Copilot for Microsoft 365—from drafting emails to summarizing documents. Get started: http://msft.it/6049YslHV #AI #Microsoft365

🎄 Day 3 of the December AI Advent Calendar: Types of AI – Narrow AI vs. Generative AI 🤖The distinction between narrow AI and generative AI is crucial in understanding the landscape of artificial intelligence. Narrow AI, also known as weak AI, is designed and trained to perform specific tasks. Examples include voice assistants like Siri or Alexa, recommendation algorithms on platforms such as Netflix, and even the increasingly sophisticated systems behind fraud detection in banking. These AIs excel in their specialized areas but lack the ability to generalize their knowledge or perform outside their predefined functions.   ✨Generative AI, on the other hand, represents a more advanced and versatile branch. These models, such as GPT-4, are capable of creating new content by learning patterns from large datasets. They can generate text, images, music, and even videos with remarkable creativity and coherence. The flexibility of generative AI allows it to be applied across various industries, from creating engaging marketing content to assisting in scientific research by hypothesizing new theories.   Start learning more about AI and what capabilities you can leverage to your advantage via https://lnkd.in/euTnpC9P 🌍 Prefer expert-led training? Skillsoft, a Global & pan-European Training Services Partner, provides tailored AI learning experiences to equip you with practical skills and insights. Explore Microsoft Data & AI training https://lnkd.in/e-PDZ9zY here you’ll gain the expertise to thrive in a data-driven world. 👌Understanding these differences helps us appreciate the current capabilities of AI and the future potential that generative AI holds. By leveraging both narrow and generative AI, we can solve complex problems and drive innovation in unprecedented ways.   #ArtificialIntelligence #NarrowAI #GenerativeAI #TechExplained #MSLearn  

Generative AI Data: I've found a very interesting AI platform. Generative AI harnesses the power of automation and human expertise. This data engine blends automation and human intelligence to produced customized training data. People who are interested in pursuing their carrer in AI, please check out their website. The picture shown below is a step by step process of how highly advanced models are created. https://lnkd.in/eHWbcFEG