Gilbane Advisor: Next token predictors, AI product fit, VIP API Mesh
This week we feature articles from Rachel Draelos, and Benedict Evans.
Additional reading comes from Walid Saba, Benj Edwards, and Daniel Tunkelang.
News comes from WordPress VIP, Trados, Snowflake, and AtScale.
Note: Taking next week off — next issue on May 15th.
All previous issues are available at https://gilbane.com/gilbane-advisor-index
Opinion / Analysis…
Human and artificial general intelligence arises from next token prediction
“This post frames and explores the hypothesis that general intelligence arises when a learning system becomes very good at next token prediction. This hypothesis is often implied, hidden, or dancing at the margins of industrial and academic AI research — but so far, I don’t think it’s received as much open discussion as I think it merits.”
Rachel Draelos, who is an MD with a PhD in Computer Science starts by pointing out that humans are next-word predictors — literally all the time. She then makes the more general case that we are token predicting the world around us through our senses, and how all of this is consistent with current neuroscience research.
An interesting read and in spite of the topic the post is easily accessible to a general audience — there are links to technical papers. (16 min)
Looking for AI use-cases
“We’ve had ChatGPT for 18 months, but what’s it for? What are the use-cases? Why isn’t it useful for everyone, right now? Do Large Language Models become universal tools that can do ‘any’ task, or do we wrap them in single-purpose apps, and build thousands of new companies around that?”
Benedict Evans is trying to figure out how the AI application market will evolve beyond niche use cases to deliver on the widely expected growth and step change. His focus on product market fit makes his article more useful than speculative. (9 min)
https://www.ben-evans.com/benedictevans/2024/4/19/looking-for-ai-use-cases
More Reading
- June announcements could be interesting… Apple releases eight small AI language models aimed at on-device use via ars technica
- LLMs and RAG are great. What’s next? Because they’re not enough. via Daniel Tunkelang
- Walid Saba wants to know what you think… A refutation of John Searle’s famous Chinese Room Argument? via Ontologik
Content technology news…
WordPress VIP introduces VIP API Mesh to enable composable digital experiences
API Mesh simplifies data integration with a single API, improves caching, supports data transformation, and is accessible to technical and non-technical users.
https://wpvip.com/2024/04/25/vip-api-mesh-composable-digital-experiences/
Trados announces Trados Studio 2024
The computer-assisted translation tool improves accessibility, democratizes access to generative AI, and increases management capabilities.
https://slator.com/trados-enhances-platform-with-new-accessibility-ai-and-management-features/
Snowflake launches Arctic, an open enterprise-grade LLM
Snowflake Arctic LLM is a part of the Snowflake Arctic model family that also include practical text-embedding models for retrieval use cases.
https://www.snowflake.com/news/snowflake-launches-arctic-the-most-open-enterprise-grade-large-language-model/
AtScale introduces Developer Community Edition for semantic modeling
The Developer Community Edition is a fully featured, free version of AtScale’s semantic layer platform, promoting collaboration and versatility.
https://www.atscale.com/press/atscale-developer-community-edition-for-semantic-modeling/
The Gilbane Advisor is authored by Frank Gilbane and is ad-free, cost-free, and curated for content, computing, web, data, and digital experience technology and information professionals. We publish recommended articles and content technology news weekly. We do not sell or share personal data.
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Originally published at https://gilbane.com on May 1, 2024.
