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    Practical AI: Machine Learning, Data Science, LLM

    Practical AI: Machine Learning, Data Science, LLM

    Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!

    Practical AI: Machine Learning, Data Science, LLM

    Wed Jul 24 2024

    Hyperventilating over the Gartner AI Hype Cycle

    AITechnologyInnovation

    The episode covers the Intel Innovation 2024 event, the Gartner hype cycle for AI, various AI technologies on the hype cycle, innovation and future trends in AI, emerging trends in AI, new AI concepts and trends, AI on the hype curve, and data leakage and AI concepts. Key insights include the challenges of replicating live events virtually, the debate around cloud AI services, the skepticism towards prompt engineering as a specialized role, and the potential growth of EQ AI (Empathetic AI).

    Practical AI: Machine Learning, Data Science, LLM

    Thu Jul 18 2024

    The first real-time voice assistant

    AIOpenAIMoshiGenerative AIBlockchain

    This episode covers a range of topics including the release of Moshi, a real-time multimodal voice assistant, the evolution of OpenAI and the future of open research, the hype cycle of generative AI, the role of blockchain and composite AI solutions, AI's impact and the debate on human creativity, and the co-creation of humans and technology. It explores the challenges and potential of AI in various industries and emphasizes the importance of integration and collaboration for successful outcomes.

    Practical AI: Machine Learning, Data Science, LLM

    Wed Jul 10 2024

    Vectoring in on Pinecone

    vector databasessemantic searchembeddingsRAGAI models

    This episode explores the world of vector databases and their role in enhancing AI models like LLMs. It covers topics such as semantic search with embeddings, leveraging RAG for more reliable answers, onboarding and implementing RAG applications, scalability and user experience with Pinecone, and the benefits of vector databases like Pinecone. The episode highlights the importance of understanding different database types and their applications in creating innovative AI solutions.

    Practical AI: Machine Learning, Data Science, LLM

    Tue Jul 02 2024

    Stanford's AI Index Report 2024

    AI Index ReportFrontier AI ResearchPlumbAI RegulationsAI Models

    The episode covers the AI Index Report, frontier AI research, Plumb and AI regulations, AI models and efficiency, evaluating AI performance, and risks and impact of AI. It discusses trends in AI development, the high costs of frontier AI research, increasing AI regulations, challenges in scaling transformer models, evaluating AI performance, and the short-term and long-term risks and impact of AI.

    Practical AI: Machine Learning, Data Science, LLM

    Tue Jun 25 2024

    Apple Intelligence & Advanced RAG

    language modelsAI adoptionApple Intelligencethird-party APIsopen models

    The episode covers challenges and nuances of using large language models, the evolving landscape of AI adoption, Apple Intelligence, challenges with third-party APIs and open models, improving RAG systems, advanced techniques for RAG systems, and closing remarks.

    Practical AI: Machine Learning, Data Science, LLM

    Wed Jun 19 2024

    The perplexities of information retrieval

    Language ModelsKnowledge GraphsProplexedLarge Language ModelsSpecialized Models

    The episode discusses the challenges and potential of language models like chat GPT, pairing them with knowledge graphs, and utilizing large language models for knowledge retrieval. It also explores the development of Proplexed as a fast and accurate answer engine. The importance of balancing general and specialized models, routing queries, improving interfaces, and moving towards perfect answers and decision-making are highlighted.

    Practical AI: Machine Learning, Data Science, LLM

    Thu Jun 13 2024

    Using edge models to find sensitive data

    AIPrivacyHealthcareData Security

    Ramin Mohamadi discusses the importance of safeguarding private AI models and the intersection of AI and privacy in handling personally identifying information (PHI) and personal health information. Healthcare organizations face challenges in detecting 'dark PHI' data and applying AI in healthcare. Model development, deployment, and monitoring in healthcare are explored. The use of AI in detecting risks and deploying models at the edge is highlighted. Challenges and success stories in working with AI models are discussed.

    Practical AI: Machine Learning, Data Science, LLM

    Tue Jun 04 2024

    Rise of the AI PC & local LLMs

    AIGPT-4.0Local AI ModelsCloud AI ModelsAI Hardware

    The episode discusses recent confusion around GPT-4.0, the trend of utilizing both local and cloud AI models, routing between local and cloud models, AI hardware and model optimization, and inference on local machines.

    Practical AI: Machine Learning, Data Science, LLM

    Wed May 29 2024

    AI in the U.S. Congress

    AI policyPolicy makersEthicsSocietal impactUS and EU policies

    This episode explores the involvement of policy makers in AI, the challenges they face in keeping up with rapid advancements, and the ethical considerations and societal impact of AI. It also delves into the comparison of US and EU AI policies, the potential misuse of AI, and the role of AI in education and healthcare.

    Practical AI: Machine Learning, Data Science, LLM

    Wed May 22 2024

    First impressions of GPT-4o

    AI-driven methodologiesGPT-4O OmniGPT-4AI applicationsEthical implications

    AI-driven methodologies are being used to explore proteins for drug candidates. The release of GPT-4O Omni has caused a stir, with its multimodal capabilities and impact on daily tasks. GPT-4 enables faster interactions across text, speech, and image modalities. Discussion on GPT 4.0 capabilities and improvements compared to previous versions. The integration of robotics and AI in retail experiences is becoming more prevalent. The release of GPT-4.0 has set new expectations for interacting with AI. Hugging Face is making GPU compute available within their environment to help beat big AI companies. Advancements in AI could change everyday life and solve big challenges facing humanity.

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