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The model can respond to various queries, but striking a balance between presenting possibilities and not definitive answers is challenging.
BARD originated from experimenting with language models in Google Assistant. It was realized that a standalone web experience for interacting with the model was the best choice.
The team focused on minimizing safety risks and managing inadvertent safety risks. They developed policies and conducted red teaming to ensure responsible use of the technology.
The team's passion for helping users and their belief in the technology's potential fueled their fast-paced development and willingness to learn and iterate quickly.
The podcast discusses the challenge of balancing user expectations of quick information with the need to provide valuable responses in a thoughtful manner. While many users prefer instant streaming of information, there are also those who appreciate receiving a complete answer once it's ready. This insight highlights the importance of understanding user preferences and determining the appropriate approach. The team also addresses the challenge of presenting information accurately, especially when faced with breaking news or sensitive topics. Striking a balance between maximizing helpfulness and minimizing potential harm remains an ongoing endeavor.
The podcast explores the important qualities and characteristics the team looked for when building Bard. They placed a strong emphasis on bias to action, ensuring that team members were motivated to learn quickly and take decisive steps. However, it was also crucial to strike a balance and avoid excessive risk-taking. The team sought individuals who valued learning responsibly and approached their work with deep understanding and thoughtfulness. While diversity within the team was important, having a common drive and passion to deliver the technology's maximum helpfulness while minimizing harm was a key factor in successful collaboration.
Jack Krawczyk is a Senior Director of Product at Google, building Bard. Bard is Google’s collaborative, conversational, and experimental AI tool that’s bridging the gap between humans and bots, while addressing ethical considerations around AI. After joining the project in 2020, Jack helped ship Bard in less than four years. Bard sources information directly from the web, and now enables users to inquire about and summarize YouTube videos.
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In today’s episode, we discuss:
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Referenced:
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Where to find Jack Krawczyk:
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Where to find Brett Berson:
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Where to find First Round Capital:
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Timestamps:
(00:00) Introduction
(02:17) Bard’s origin story
(03:54) Deciding on the application of Bard
(05:59) The ethical considerations around building Bard
(10:19) Why Bard launched to the public so early
(13:30) Risk-taking at big companies versus smaller ones
(16:20) Bard’s early user research
(21:21) Bard versus ChatGPT
(25:01) The cultural and product principles behind Bard
(30:56) Insight into Bard’s impressive development speed
(35:17) Deciding when to ship Bard
(41:41) Why Bard is different from other products Jack has built
(46:30) Evaluating Bard’s original spec
(48:02) Insight into Bard's product roadmap
(56:00) The toughest challenges Bard has faced
(57:50) What’s special about team-building at Bard
(62:54) Addressing Bard’s negative press
(67:49) Advice for aspiring LLM companies
(69:15) Advice for non-LLM companies
(71:05) The biggest barriers to advancing AI
(75:45) How product people can use or build with AI
(77:24) How AI is changing product leadership
(79:20) People who had an outsized impact on Jack
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