In 2017, Google invented Transformer architecture for powering large language models and published a seminal paper, Attention is All You Need. The following year, they opensourced BERT which became the world's first widely adopted LLM and brought it into Google Search. Now, Google Cloud has opened up the infrastructure, search, and models behind Google.com to customers, developers, and partners including Salesforce's Einstein 1 Platform. Google Cloud CEO Thomas Kurian joins Clara to discuss the challenges, opportunities, and prerequisites for companies to successfully deploy AI. They discuss the importance of organizing structured and unstructured data as inputs into model training and prompts, Google's innovative LoRA method for costeffectively finetuning models, the role of agents in daytoday tasks, and innovations for responsible AI deployment such as watermarking.

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Chapters:
0:00 Introduction
1:03 How Google Cloud works with other Google products
3:30 Where should customers start with AI?
4:53 How to prep your data for AI
6:57 Google and Salesforce partnership
12:13 Finetune data vs. augmented generation
14:20 Lowrank adaptation (LoRA) technique
18:53 AI agents that have individual personalities
24:35 The future of software development
27:05 Risks with AI
29:12 How did your childhood shape your career?
31:20 How should we educate our kids about an AIdriven world?
34:20 Three takeaways from Clara Shih

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