The Download: the next big thing in LLMs and how AI academic research is shifti
The DownloadThe Download: the next big thing in LLMs and how AI academic research is shiftingPlus: Nvidia has secured $500 billion from Wall Street for AI infrastructure. These startups are chasing the next big thing in LLMs Nine years after Google researchers introduced the transformer, this family of neural networks has become the engine inside every major large language model. But transformers are starting to show their age.
- ▪The DownloadThe Download: the next big thing in LLMs and how AI academic research is shiftingPlus: Nvidia has secured $500 billion from Wall Street for AI infrastructure.
- ▪These startups are chasing the next big thing in LLMs Nine years after Google researchers introduced the transformer, this family of neural networks has become the engine inside every major large language model.
- ▪But transformers are starting to show their age.
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,495 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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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 | MIT Technology Review |
| Canonical URL | https://www.technologyreview.com/2026/08/11/1141610/the-download-next-big-thing-llms-ai-academic-research-shifting/ |
| Publication time | Tue, 11 Aug 2026 17:01:01 +0000 |
| Retrieval time | 2026-08-11T17:10:44.258Z |
| Last seen | 2026-08-11T17:10:44.258Z |
| 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 | 7VDlKaCBt2l8 · 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
The DownloadThe Download: the next big thing in LLMs and how AI academic research is shiftingPlus: Nvidia has secured $500 billion from Wall Street for AI infrastructure. By Thomas Macaulayarchive pageAugust 11, 2026 This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. These startups are chasing the next big thing in LLMs Nine years after Google researchers introduced the transformer, this family of neural networks has become the engine inside every major large language model. But transformers are starting to show their age. As LLMs get bigger and better, transformers have become a bottleneck.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at MIT Technology Review.
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