Ask HN: How are much smarter AI models made?
I am curious what actually happens between two generations of AI models.For example, how do you go from Sonnet to Opus? Is Opus trained from scratch, built on Sonnet, or mostly the same model with more compute and training?And how do models like Astra suddenly make a big jump in some capabilities? What is stopping Anthropic, Mistral, or others from doing the same thing?
- ▪I am curious what actually happens between two generations of AI models.For example, how do you go from Sonnet to Opus?
- ▪Is Opus trained from scratch, built on Sonnet, or mostly the same model with more compute and training?And how do models like Astra suddenly make a big jump in some capabilities?
- ▪What is stopping Anthropic, Mistral, or others from doing the same thing?
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,494 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Ycombinator |
| Canonical URL | https://news.ycombinator.com/item?id=49662978 |
| Publication time | Fri, 11 Sep 2026 18:24:20 +0000 |
| Retrieval time | 2026-09-11T18:53:48.321Z |
| Last seen | 2026-09-11T18:54:06.485Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | cXQlGlvRfWqb · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
I am curious what actually happens between two generations of AI models.For example, how do you go from Sonnet to Opus? Is Opus trained from scratch, built on Sonnet, or mostly the same model with more compute and training?And how do models like Astra suddenly make a big jump in some capabilities? What is stopping Anthropic, Mistral, or others from doing the same thing? Is the main difference just more compute and money, or are there training methods, data, architecture, and research breakthroughs that competitors may not know about?I can't think of a better place to ask this. I am guessing there are people here who actually work on these models and know what goes on behind the scenes.
Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.