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内容由Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang提供。所有播客内容(包括剧集、图形和播客描述)均由 Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
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LLMs are like your weird, over-confident intern | Simon Willison (Datasette)

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Manage episode 439118935 series 2838288
内容由Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang提供。所有播客内容(包括剧集、图形和播客描述)均由 Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Known for co-creating Django and Datasette, as well as his thoughtful writing on LLMs, Simon Willison joins the show to chat about blogging as an accountability mechanism, how to build intuition with LLMs, building a startup with his partner on their honeymoon, and more.

Segments:

(00:00:00) The weird intern

(00:01:50) The early days of LLMs

(00:04:59) Blogging as an accountability mechanism

(00:09:24) The low-pressure approach to blogging

(00:11:47) GitHub issues as a system of records

(00:16:15) Temporal documentation and design docs

(00:18:19) GitHub issues for team collaboration

(00:21:53) Copy-paste as an API

(00:26:54) Observable notebooks

(00:28:50) pip install LLM

(00:32:26) The evolution of using LLMs daily

(00:34:47) Building intuition with LLMs

(00:43:24) Democratizing access to automation

(00:47:45) Alternative interfaces for language models

(00:53:39) Is prompt engineering really engineering?

(00:58:39) The frustrations of working with LLMs

(01:01:59) Structured data extraction with LLMs

(01:06:08) How Simon would go about building a LLM app

(01:09:49) LLMs making developers more ambitious

(01:13:32) Typical workflow with LLMs

(01:19:58) Vibes-based evaluation

(01:23:25) Staying up-to-date with LLMs

(01:27:49) The impact of LLMs on new programmers

(01:29:37) The rise of 'Goop' and the future of software development

(01:40:20) Being an independent developer

(01:42:26) Staying focused and accountable

(01:47:30) Building a startup with your partner on the honeymoon

(01:51:30) The responsibility of AI practitioners

(01:53:07) The hidden dangers of prompt injection

(01:53:44) “Artificial intelligence” is really “imitation intelligence”

Show Notes:

Simon’s blog: https://simonwillison.net/

Natalie’s post on them building a startup together: https://blog.natbat.net/post/61658401806/lanyrd-from-idea-to-exit

Simon’s talk from DjangoCon: https://www.youtube.com/watch?v=GLkRK2rJGB0

Simon on twitter: https://x.com/simonw

Datasette: https://github.com/simonw/datasette

Stay in touch:

👋 Make Ronak’s day by leaving us a review and let us know who we should talk to next! hello@softwaremisadventures.com

Music: Vlad Gluschenko — Forest License: Creative Commons Attribution 3.0 Unported: https://creativecommons.org/licenses/by/3.0/deed.en

  continue reading

53集单集

Artwork
icon分享
 
Manage episode 439118935 series 2838288
内容由Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang提供。所有播客内容(包括剧集、图形和播客描述)均由 Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Known for co-creating Django and Datasette, as well as his thoughtful writing on LLMs, Simon Willison joins the show to chat about blogging as an accountability mechanism, how to build intuition with LLMs, building a startup with his partner on their honeymoon, and more.

Segments:

(00:00:00) The weird intern

(00:01:50) The early days of LLMs

(00:04:59) Blogging as an accountability mechanism

(00:09:24) The low-pressure approach to blogging

(00:11:47) GitHub issues as a system of records

(00:16:15) Temporal documentation and design docs

(00:18:19) GitHub issues for team collaboration

(00:21:53) Copy-paste as an API

(00:26:54) Observable notebooks

(00:28:50) pip install LLM

(00:32:26) The evolution of using LLMs daily

(00:34:47) Building intuition with LLMs

(00:43:24) Democratizing access to automation

(00:47:45) Alternative interfaces for language models

(00:53:39) Is prompt engineering really engineering?

(00:58:39) The frustrations of working with LLMs

(01:01:59) Structured data extraction with LLMs

(01:06:08) How Simon would go about building a LLM app

(01:09:49) LLMs making developers more ambitious

(01:13:32) Typical workflow with LLMs

(01:19:58) Vibes-based evaluation

(01:23:25) Staying up-to-date with LLMs

(01:27:49) The impact of LLMs on new programmers

(01:29:37) The rise of 'Goop' and the future of software development

(01:40:20) Being an independent developer

(01:42:26) Staying focused and accountable

(01:47:30) Building a startup with your partner on the honeymoon

(01:51:30) The responsibility of AI practitioners

(01:53:07) The hidden dangers of prompt injection

(01:53:44) “Artificial intelligence” is really “imitation intelligence”

Show Notes:

Simon’s blog: https://simonwillison.net/

Natalie’s post on them building a startup together: https://blog.natbat.net/post/61658401806/lanyrd-from-idea-to-exit

Simon’s talk from DjangoCon: https://www.youtube.com/watch?v=GLkRK2rJGB0

Simon on twitter: https://x.com/simonw

Datasette: https://github.com/simonw/datasette

Stay in touch:

👋 Make Ronak’s day by leaving us a review and let us know who we should talk to next! hello@softwaremisadventures.com

Music: Vlad Gluschenko — Forest License: Creative Commons Attribution 3.0 Unported: https://creativecommons.org/licenses/by/3.0/deed.en

  continue reading

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