Practical AI

Benjamin Consolvo, AI engineering manager at Intel, and Greg Serochi, Developer ecosystem manager at Intel Gaudi, dive into Intel's cutting-edge AI strategy. They discuss Gaudi processors as an innovative alternative for AI workloads on CPUs, rivaling traditional GPU solutions. Insights on open-source collaborations with Hugging Face highlight their community-driven approach. The duo elaborates on practical applications of Intel's technology in deep learning and computer vision, shaping the future of AI integration and deployment.

Join Bengsoon Chuah, a data scientist in the energy sector, as he dives into the world of practical AI. He discusses the concept of 'Broccoli AI'—healthy AI for businesses. Bengsoon shares insights on deploying NLP pipelines in on-prem environments and navigating challenges like limited cloud access. He emphasizes the integration of machine learning with existing data and the vital role of subject matter experts in analyzing unstructured data for safety. Get ready for innovative strategies in AI deployment and project management!

Demetrios Brinkmann, a member of the MLOps Community and a frequent voice in AI discussions, joins Daniel and Chris for a lively chat about the 2024 Gartner Hype Cycle. They humorously dissect the hype surrounding various AI technologies, like cloud AI services and generative AI. The trio highlights the absence of ethical considerations in the cycle and debates the practical limitations of small models in consumer devices. With engaging insights, they question the future of sustainable AI and the role of community in navigating these innovations.

The discussion kicks off with a light-hearted take on AI's potential, including a humorous nod to weather manipulation. A groundbreaking real-time voice assistant, Moshi, is unveiled, positioning itself against major players like GPT-4. The conversation navigates the evolving AI landscape, emphasizing the importance of open engagement. Insights on low-code solutions like Plum highlight how they ease complex AI adoption. The hosts also explore the Gartner hype cycle, drawing parallels between AI's evolution and the internet revolution, and tackle the interplay between AI and human creativity.

In this engaging discussion, Roie Schwaber-Cohen, a developer advocate at Pinecone and an expert in vector databases, highlights the transformative power of vector databases in AI. He explains how Pinecone enhances data interactions for large language models through embeddings, allowing for improved semantic search that can uncover unexpected connections. Roie also discusses Pinecone's serverless evolution, making it scalable and user-friendly, and shares insights on the future of AI technologies and the need for continuous adaptation in data management.

Nestor Maslej, Research Manager at Stanford’s Institute for Human-Centered AI, shares insights from the 2024 AI Index Report. They discuss how AI increases worker productivity and the growing regulatory landscape in the U.S. Industry is currently leading frontier AI research, raising questions about sustainability as financial investments soar. Maslej emphasizes the need for responsible policymaking and community engagement as AI evolves, highlighting the importance of collaboration across sectors.

Dive into the evolving landscape of AI in enterprises and the nuances of Apple's latest advancements in AI strategy. Explore how organizations are balancing the hype of AI adoption with real-world challenges, while emphasizing user control and privacy. Discover advanced techniques in Retrieval Augmented Generation to enhance workflow and accuracy in data retrieval. The hosts also unpack methods for integrating dynamic data into AI prompts, driving deeper insights and improving model responses.

Denis Yarats, co-founder and CTO of Perplexity, dives deep into the world of AI-driven information retrieval. He highlights the shortcomings of traditional search engines and reveals how Perplexity aims to enhance accuracy and validation. The conversation explores the challenges of integrating large language models for real-time data access and the importance of verifying generated content. Denis also shares insights on future innovations in user experience design and the potential for AI to improve decision-making by synthesizing information into actionable insights.

Ramin Mohammadi, AI and ML lead at TauSight and adjunct professor at Northeastern, discusses the critical intersection of AI and privacy, particularly in handling sensitive health information. He highlights the alarming rise in healthcare data breaches and the challenges of managing unstructured data. Ramin explains how edge AI models can enhance the detection of protected health information, addressing limitations of traditional methods. He shares insights on the promise of smaller models and federated learning in bolstering data security within healthcare.

Explore the surge in local AI models and their fascinating integration into AI PCs from tech giants like NVIDIA, Apple, and Intel. Discover the benefits and challenges of running AI models locally versus in the cloud, as well as the importance of optimizing hardware for better performance. Learn about the benchmarks being established for AI workloads and how these advancements are reshaping the future of technology. Dive into the world of large language models and their promise to refine AI capabilities, including overcoming common challenges.