Learning to Love AI, AI-powered Enterprise Search, and Data Pruning
Learning to Love AI, AI-powered Enterprise Search, and Data Pruning
AI Bytes: Volume CI, Issue #12
Get smarter faster with AI Bytes: 3 articles, 2 podcasts, and 1 video.
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READING
III. What Is ChatGPT Doing … and Why Does It Work?
Stephen Wolfram discusses the success of ChatGPT, a neural network designed to generate human-like language, and what it reveals about the structure of human language. He explores the idea of a semantic grammar and computational language, and how they can be used to construct a more complete system for generating meaningful text. Stephen also discusses the limitations of ChatGPT and the potential for future improvements. Overall, the success of ChatGPT suggests that human language is simpler and more structured than previously thought.
II. Why we should stop worrying and learn to love AI
Om Malik argues we should think of AI as "augmented intelligence" rather than "artificial intelligence" and focus on the positive impacts. He cites examples of AI being used to identify signs of breast cancer and discover antimicrobial resistance, as well as automate complex and repetitive tasks. The bottom line is AI can help us make sense of our data-saturated world and improve our lives.
I. Blender can now use AI to create images and effects from text descriptions
Stability AI has introduced a tool called Stability for Blender that allows users to create AI-based textures, effects, and animations using source material from renders or text descriptions. The tool is free to use and does not require software dependencies or a dedicated GPU. It can save time and money, and may help streamline work for those already planning to use AI-generated art. However, it won't create 3D objects from scratch and is unlikely to give Stable Diffusion a major advantage over rivals like OpenAI's DALL-E.
LISTENING
II. Glean Founders Talk AI-Powered Enterprise Search
This podcast discusses the potential of large language models (LLMs) to improve enterprise search by indexing all accessible company data, including Slack, Dropbox, and email. The founders of Glean, a Silicon Valley startup focused on enterprise search, discuss the challenges and opportunities of implementing LLMs in the workplace and how they can help knowledge workers spend less time searching and more time working.
In this episode, Ben Sorscher, a PhD student at Stanford, talks about reducing the size of data sets used to train models, particularly large language models, which are pushing the limits of scaling because of the enormous cost of training and the environmental impact of generating the electricity they consume.
WATCHING
I. Watch me create a Children's Book with Mid-Journey in 10 minutes
ICYMI
NeoSwap AI Bags $2M Pre-seed Investment for AI-powered NFT Trading
The Ghost in the Machine, SwitchPrompting, NLP Solutions, and Installing Stable Diffusion Locally
AI-powered Productivity/Storytelling App Tome Raises $43M Series B
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