Latest in AI Models & Deployment

12 個內容
March 2024
, VP, Applied Deep Learning Research, NVIDIA
, Founder and Chief Executive Officer, Adept AI
2024 is the year of multimodal models--ones that understand images as well as text — and the first year that AI agents are becoming mature enough to be useful. But are they enough to get us to artificial general intelligence (AGI)? Join this discussion from Bryan, the head of deep learning for NVIDIA, and
March 2024
, NVIDIA
, Principal Software Architect, NVIDIA
, Senior Software Engineer, NVIDIA
Learn how to serve large language models (LLMs) efficiently using Triton Inference Server with step-by-step instructions. NVIDIA Triton Inference Server is an open-source inference serving solution that simplifies the production deployment of AI models at scale. With a uniform interface and standard set
March 2024
, Vice President and General Manager of Retail and CPG, NVIDIA
, Executive Vice President, Chief Digital and Information Officer, Lowe's
Lowe’s remains at the forefront of transformation by constantly exploring emerging technologies that help advance its business. An early explorer of AI, the Fortune 50 home improvement company continues to enhance the omnichannel experience for customers and associates. From better
March 2024
, Strategic AI Lead, NVIDIA
, Co-Founder and Co-CEO, AI21 Labs
Join this discussion from Vartika, leader of strategic AI at NVIDIA, and Yoav, computer scientist and co-founder of AI21, as they discuss how we can go beyond large language models (LLMs) and delve into a world of AI that understands.
March 2024
, VP of Product, Core ML/AI, Google
In an era where 'Artificial Intelligence' is not just a buzzword but a core component of every product roadmap, how do we navigate this new central role of AI in product development? As an “AI insider”, Xavier Amatriain has witnessed firsthand the seismic shifts brought about by the AI revolution,
March 2024
, Executive Director, Artificial Intelligence, Ford Motor Co.
Large language models (LLM) are revolutionizing the way we interact with information, making it easy to pinpoint information from a large source of data, such as vehicle owner’s manuals or manufacturing machinery manuals. However, ensuring these agents operate accurately, or without hallucinating,
March 2024
, Vice President, AI Research, Meta
We've seen incredible progress in the last year in large AI models, with increasing abilities to generate high-quality images, videos, text, sound, and more. The best of these models display signs of creativity, reasoning, generalization, and plasticity beyond what we could imagine just a few years ago. Yet many
March 2024
, CEO, Salesforce AI
, CIO & Senior Vice President, Adobe
, Executive Vice President and Chief Technology Officer, Intuit
, Sr. Director, AI and Legal Ethics, NVIDIA
, VP Strategic Technologies, Autodesk
, Executive Vice President, Artificial Intelligence, Mastercard
In the panel discussion, industry experts will share their insights and strategies for promoting innovation within organizations. The panelists will delve into the challenges of breaking down silos, addressing legacy systems, and managing technical debt. They will also explore the importance of cultivating a
March 2024
, Research Scientist and Co-Founder, xAI
, Data Scientist, NVIDIA
Christian Szegedy is a research scientist and cofounder at xAI. Over the past seven years, Christian's main focus has been on AI-based reasoning, and especially on the automated formalization of mathematics. This is a very intriguing line of work that holds strong potential for software synthesis
March 2024
, Vice President, Microsoft GenAI
Large language models (LLMs) have taken the field of AI by storm. But how large do they really need to be? I'll discuss the phi series of models from Microsoft Research, which exhibit many of the striking emergent properties of LLMs despite having a mere 1 billion parameters.
March 2024
, CEO, Mistral AI
Mistral AI trains state-of-the-art generative models with a strong emphasis on customization and control. It has released the best open-source models as of today. In this keynote, we'll reflect on the scientific lessons we learned while training our first models (Mistral and Mixtral) and give a glimpse of what's
March 2024
, Machine Learning Engineer, PolyAI
There are an increasing number of out-of-the-box automatic speech recognition (ASR) solutions to support new and innovative conversational applications across the enterprise landscape. While their performance is generally satisfactory for many uses, there are real limitations when applying them to